--- title: Agents Changelog image: https://developers.cloudflare.com/cf-twitter-card.png --- [Skip to content](#%5Ftop) # Changelog New updates and improvements at Cloudflare. [ Subscribe to RSS ](https://developers.cloudflare.com/changelog/rss/index.xml) [ View RSS feeds ](https://developers.cloudflare.com/fundamentals/new-features/available-rss-feeds/) Agents ![hero image](https://developers.cloudflare.com/_astro/hero.CVYJHPAd_26AMqX.svg) Mar 23, 2026 1. ### [Agents SDK v0.8.0: readable state, idempotent schedules, typed AgentClient, and Zod 4](https://developers.cloudflare.com/changelog/post/2026-03-23-agents-sdk-v080/) [ Agents ](https://developers.cloudflare.com/agents/)[ Workers ](https://developers.cloudflare.com/workers/) The latest release of the [Agents SDK ↗](https://github.com/cloudflare/agents) exposes agent state as a readable property, prevents duplicate schedule rows across Durable Object restarts, brings full TypeScript inference to `AgentClient`, and migrates to Zod 4. #### Readable `state` on `useAgent` and `AgentClient` Both `useAgent` (React) and `AgentClient` (vanilla JS) now expose a `state` property that reflects the current agent state. Previously, reading state required manually tracking it through the `onStateUpdate` callback. **React (`useAgent`)** * [ JavaScript ](#tab-panel-324) * [ TypeScript ](#tab-panel-325) JavaScript ``` const agent = useAgent({ agent: "game-agent", name: "room-123", }); // Read state directly — no separate useState + onStateUpdate needed return
Score: {agent.state?.score}
; // Spread for partial updates agent.setState({ ...agent.state, score: (agent.state?.score ?? 0) + 10 }); ``` TypeScript ``` const agent = useAgent({ agent: "game-agent", name: "room-123", }); // Read state directly — no separate useState + onStateUpdate needed return
Score: {agent.state?.score}
; // Spread for partial updates agent.setState({ ...agent.state, score: (agent.state?.score ?? 0) + 10 }); ``` `agent.state` is reactive — the component re-renders when state changes from either the server or a client-side `setState()` call. **Vanilla JS (`AgentClient`)** * [ JavaScript ](#tab-panel-326) * [ TypeScript ](#tab-panel-327) JavaScript ``` const client = new AgentClient({ agent: "game-agent", name: "room-123", host: "your-worker.workers.dev", }); client.setState({ score: 100 }); console.log(client.state); // { score: 100 } ``` TypeScript ``` const client = new AgentClient({ agent: "game-agent", name: "room-123", host: "your-worker.workers.dev", }); client.setState({ score: 100 }); console.log(client.state); // { score: 100 } ``` State starts as `undefined` and is populated when the server sends the initial state on connect (from `initialState`) or when `setState()` is called. Use optional chaining (`agent.state?.field`) for safe access. The `onStateUpdate` callback continues to work as before — the new `state` property is additive. #### Idempotent `schedule()` `schedule()` now supports an `idempotent` option that deduplicates by `(type, callback, payload)`, preventing duplicate rows from accumulating when called in places that run on every Durable Object restart such as `onStart()`. **Cron schedules are idempotent by default.** Calling `schedule("0 * * * *", "tick")` multiple times with the same callback, expression, and payload returns the existing schedule row instead of creating a new one. Pass `{ idempotent: false }` to override. Delayed and date-scheduled types support opt-in idempotency: * [ JavaScript ](#tab-panel-328) * [ TypeScript ](#tab-panel-329) JavaScript ``` import { Agent } from "agents"; class MyAgent extends Agent { async onStart() { // Safe across restarts — only one row is created await this.schedule(60, "maintenance", undefined, { idempotent: true }); } } ``` TypeScript ``` import { Agent } from "agents"; class MyAgent extends Agent { async onStart() { // Safe across restarts — only one row is created await this.schedule(60, "maintenance", undefined, { idempotent: true }); } } ``` Two new warnings help catch common foot-guns: * Calling `schedule()` inside `onStart()` without `{ idempotent: true }` emits a `console.warn` with actionable guidance (once per callback; skipped for cron and when `idempotent` is set explicitly). * If an alarm cycle processes 10 or more stale one-shot rows for the same callback, the SDK emits a `console.warn` and a `schedule:duplicate_warning` diagnostics channel event. #### Typed `AgentClient` with `call` inference and `stub` proxy `AgentClient` now accepts an optional agent type parameter for full type inference on RPC calls, matching the typed experience already available with `useAgent`. * [ JavaScript ](#tab-panel-332) * [ TypeScript ](#tab-panel-333) JavaScript ``` const client = new AgentClient({ agent: "my-agent", host: window.location.host, }); // Typed call — method name autocompletes, args and return type inferred const value = await client.call("getValue"); // Typed stub — direct RPC-style proxy await client.stub.getValue(); await client.stub.add(1, 2); ``` TypeScript ``` const client = new AgentClient({ agent: "my-agent", host: window.location.host, }); // Typed call — method name autocompletes, args and return type inferred const value = await client.call("getValue"); // Typed stub — direct RPC-style proxy await client.stub.getValue(); await client.stub.add(1, 2); ``` State is automatically inferred from the agent type, so `onStateUpdate` is also typed: * [ JavaScript ](#tab-panel-330) * [ TypeScript ](#tab-panel-331) JavaScript ``` const client = new AgentClient({ agent: "my-agent", host: window.location.host, onStateUpdate: (state) => { // state is typed as MyAgent's state type }, }); ``` TypeScript ``` const client = new AgentClient({ agent: "my-agent", host: window.location.host, onStateUpdate: (state) => { // state is typed as MyAgent's state type }, }); ``` Existing untyped usage continues to work without changes. The RPC type utilities (`AgentMethods`, `AgentStub`, `RPCMethods`) are now exported from `agents/client` for advanced typing scenarios.`agents`, `@cloudflare/ai-chat`, and `@cloudflare/codemode` now require `zod ^4.0.0`. Zod v3 is no longer supported. #### `@cloudflare/ai-chat` fixes * **Turn serialization** — `onChatMessage()` and `_reply()` work is now queued so user requests, tool continuations, and `saveMessages()` never stream concurrently. * **Duplicate messages on stop** — Clicking stop during an active stream no longer splits the assistant message into two entries. * **Duplicate messages after tool calls** — Orphaned client IDs no longer leak into persistent storage. #### `keepAlive()` and `keepAliveWhile()` are no longer experimental `keepAlive()` now uses a lightweight in-memory ref count instead of schedule rows. Multiple concurrent callers share a single alarm cycle. The `@experimental` tag has been removed from both `keepAlive()` and `keepAliveWhile()`. #### `@cloudflare/codemode`: TanStack AI integration A new entry point `@cloudflare/codemode/tanstack-ai` adds support for [TanStack AI's ↗](https://tanstack.com/ai) `chat()` as an alternative to the Vercel AI SDK's `streamText()`: * [ JavaScript ](#tab-panel-338) * [ TypeScript ](#tab-panel-339) JavaScript ``` import { createCodeTool, tanstackTools, } from "@cloudflare/codemode/tanstack-ai"; import { chat } from "@tanstack/ai"; const codeTool = createCodeTool({ tools: [tanstackTools(myServerTools)], executor, }); const stream = chat({ adapter, tools: [codeTool], messages }); ``` TypeScript ``` import { createCodeTool, tanstackTools } from "@cloudflare/codemode/tanstack-ai"; import { chat } from "@tanstack/ai"; const codeTool = createCodeTool({ tools: [tanstackTools(myServerTools)], executor, }); const stream = chat({ adapter, tools: [codeTool], messages }); ``` #### Upgrade To update to the latest version: Terminal window ``` npm i agents@latest @cloudflare/ai-chat@latest ``` Mar 17, 2026 1. ### [@cloudflare/codemode v0.2.1: MCP barrel export, zero-dependency main entry point, and custom sandbox modules](https://developers.cloudflare.com/changelog/post/2026-03-17-codemode-sdk-v021/) [ Agents ](https://developers.cloudflare.com/agents/)[ Workers ](https://developers.cloudflare.com/workers/) The latest releases of [@cloudflare/codemode ↗](https://www.npmjs.com/package/@cloudflare/codemode) add a new MCP barrel export, remove `ai` and `zod` as required peer dependencies from the main entry point, and give you more control over the sandbox. #### New `@cloudflare/codemode/mcp` export A new `@cloudflare/codemode/mcp` entry point provides two functions that wrap MCP servers with Code Mode: * **`codeMcpServer({ server, executor })`** — wraps an existing MCP server with a single `code` tool where each upstream tool becomes a typed `codemode.*` method. * **`openApiMcpServer({ spec, executor, request })`** — creates `search` and `execute` MCP tools from an OpenAPI spec with host-side request proxying and automatic `$ref` resolution. * [ JavaScript ](#tab-panel-336) * [ TypeScript ](#tab-panel-337) JavaScript ``` import { codeMcpServer } from "@cloudflare/codemode/mcp"; import { DynamicWorkerExecutor } from "@cloudflare/codemode"; const executor = new DynamicWorkerExecutor({ loader: env.LOADER }); // Wrap an existing MCP server — all its tools become // typed methods the LLM can call from generated code const server = await codeMcpServer({ server: upstreamMcp, executor }); ``` TypeScript ``` import { codeMcpServer } from "@cloudflare/codemode/mcp"; import { DynamicWorkerExecutor } from "@cloudflare/codemode"; const executor = new DynamicWorkerExecutor({ loader: env.LOADER }); // Wrap an existing MCP server — all its tools become // typed methods the LLM can call from generated code const server = await codeMcpServer({ server: upstreamMcp, executor }); ``` #### Zero-dependency main entry point **Breaking change in v0.2.0:** `generateTypes` and the `ToolDescriptor` / `ToolDescriptors` types have moved to `@cloudflare/codemode/ai`: * [ JavaScript ](#tab-panel-334) * [ TypeScript ](#tab-panel-335) JavaScript ``` // Before import { generateTypes } from "@cloudflare/codemode"; // After import { generateTypes } from "@cloudflare/codemode/ai"; ``` TypeScript ``` // Before import { generateTypes } from "@cloudflare/codemode"; // After import { generateTypes } from "@cloudflare/codemode/ai"; ``` The main entry point (`@cloudflare/codemode`) no longer requires the `ai` or `zod` peer dependencies. It now exports: | Export | Description | | --------------------------- | ----------------------------------------------------------- | | sanitizeToolName | Sanitize tool names into valid JS identifiers | | normalizeCode | Normalize LLM-generated code into async arrow functions | | generateTypesFromJsonSchema | Generate TypeScript type definitions from plain JSON Schema | | jsonSchemaToType | Convert a single JSON Schema to a TypeScript type string | | DynamicWorkerExecutor | Sandboxed code execution via Dynamic Worker Loader | | ToolDispatcher | RPC target for dispatching tool calls from sandbox to host | The `ai` and `zod` peer dependencies are now optional — only required when importing from `@cloudflare/codemode/ai`. #### Custom sandbox modules `DynamicWorkerExecutor` now accepts an optional `modules` option to inject custom ES modules into the sandbox: * [ JavaScript ](#tab-panel-340) * [ TypeScript ](#tab-panel-341) JavaScript ``` const executor = new DynamicWorkerExecutor({ loader: env.LOADER, modules: { "utils.js": `export function add(a, b) { return a + b; }`, }, }); // Sandbox code can then: import { add } from "utils.js" ``` TypeScript ``` const executor = new DynamicWorkerExecutor({ loader: env.LOADER, modules: { "utils.js": `export function add(a, b) { return a + b; }`, }, }); // Sandbox code can then: import { add } from "utils.js" ``` #### Internal normalization and sanitization `DynamicWorkerExecutor` now normalizes code and sanitizes tool names internally. You no longer need to call `normalizeCode()` or `sanitizeToolName()` before passing code and functions to `execute()`. #### Upgrade Terminal window ``` npm i @cloudflare/codemode@latest ``` See the [Code Mode documentation](https://developers.cloudflare.com/agents/api-reference/codemode/) for the full API reference. Mar 03, 2026 1. ### [Real-time file watching in Sandboxes](https://developers.cloudflare.com/changelog/post/2026-03-03-sandbox-watch-file-events/) [ Agents ](https://developers.cloudflare.com/agents/) [Sandboxes](https://developers.cloudflare.com/sandbox/) now support real-time filesystem watching via `sandbox.watch()`. The method returns a [Server-Sent Events ↗](https://developer.mozilla.org/en-US/docs/Web/API/Server-sent%5Fevents) stream backed by native inotify, so your Worker receives `create`, `modify`, `delete`, and `move` events as they happen inside the container. #### `sandbox.watch(path, options)` Pass a directory path and optional filters. The returned stream is a standard `ReadableStream` you can proxy directly to a browser client or consume server-side. * [ JavaScript ](#tab-panel-342) * [ TypeScript ](#tab-panel-343) JavaScript ``` // Stream events to a browser client const stream = await sandbox.watch("/workspace/src", { recursive: true, include: ["*.ts", "*.js"], }); return new Response(stream, { headers: { "Content-Type": "text/event-stream" }, }); ``` TypeScript ``` // Stream events to a browser client const stream = await sandbox.watch("/workspace/src", { recursive: true, include: ["*.ts", "*.js"], }); return new Response(stream, { headers: { "Content-Type": "text/event-stream" }, }); ``` #### Server-side consumption with `parseSSEStream` Use `parseSSEStream` to iterate over events inside a Worker without forwarding them to a client. * [ JavaScript ](#tab-panel-344) * [ TypeScript ](#tab-panel-345) JavaScript ``` import { parseSSEStream } from "@cloudflare/sandbox"; const stream = await sandbox.watch("/workspace/src", { recursive: true }); for await (const event of parseSSEStream(stream)) { console.log(event.type, event.path); } ``` TypeScript ``` import { parseSSEStream } from "@cloudflare/sandbox"; import type { FileWatchSSEEvent } from "@cloudflare/sandbox"; const stream = await sandbox.watch("/workspace/src", { recursive: true }); for await (const event of parseSSEStream(stream)) { console.log(event.type, event.path); } ``` Each event includes a `type` field (`create`, `modify`, `delete`, or `move`) and the affected `path`. Move events also include a `from` field with the original path. #### Options | Option | Type | Description | | --------- | ---------- | ----------------------------------------------------------- | | recursive | boolean | Watch subdirectories. Defaults to false. | | include | string\[\] | Glob patterns to filter events. Omit to receive all events. | #### Upgrade To update to the latest version: Terminal window ``` npm i @cloudflare/sandbox@latest ``` For full API details, refer to the [Sandbox file watching reference](https://developers.cloudflare.com/sandbox/api/file-watching/). Mar 02, 2026 1. ### [Agents SDK v0.7.0: Observability rewrite, keepAlive, and waitForMcpConnections](https://developers.cloudflare.com/changelog/post/2026-03-02-agents-sdk-v070/) [ Agents ](https://developers.cloudflare.com/agents/)[ Workers ](https://developers.cloudflare.com/workers/) The latest release of the [Agents SDK ↗](https://github.com/cloudflare/agents) rewrites observability from scratch with `diagnostics_channel`, adds `keepAlive()` to prevent Durable Object eviction during long-running work, and introduces `waitForMcpConnections` so MCP tools are always available when `onChatMessage` runs. #### Observability rewrite The previous observability system used `console.log()` with a custom `Observability.emit()` interface. v0.7.0 replaces it with structured events published to [diagnostics channels](https://developers.cloudflare.com/workers/runtime-apis/nodejs/diagnostics-channel/) — silent by default, zero overhead when nobody is listening. Every event has a `type`, `payload`, and `timestamp`. Events are routed to seven named channels: | Channel | Event types | | ---------------- | ------------------------------------------------------------------------------------------------------------------------------------------------ | | agents:state | state:update | | agents:rpc | rpc, rpc:error | | agents:message | message:request, message:response, message:clear, message:cancel, message:error, tool:result, tool:approval | | agents:schedule | schedule:create, schedule:execute, schedule:cancel, schedule:retry, schedule:error, queue:retry, queue:error | | agents:lifecycle | connect, destroy | | agents:workflow | workflow:start, workflow:event, workflow:approved, workflow:rejected, workflow:terminated, workflow:paused, workflow:resumed, workflow:restarted | | agents:mcp | mcp:client:preconnect, mcp:client:connect, mcp:client:authorize, mcp:client:discover | Use the typed `subscribe()` helper from `agents/observability` for type-safe access: * [ JavaScript ](#tab-panel-354) * [ TypeScript ](#tab-panel-355) JavaScript ``` import { subscribe } from "agents/observability"; const unsub = subscribe("rpc", (event) => { if (event.type === "rpc") { console.log(`RPC call: ${event.payload.method}`); } if (event.type === "rpc:error") { console.error( `RPC failed: ${event.payload.method} — ${event.payload.error}`, ); } }); // Clean up when done unsub(); ``` TypeScript ``` import { subscribe } from "agents/observability"; const unsub = subscribe("rpc", (event) => { if (event.type === "rpc") { console.log(`RPC call: ${event.payload.method}`); } if (event.type === "rpc:error") { console.error( `RPC failed: ${event.payload.method} — ${event.payload.error}`, ); } }); // Clean up when done unsub(); ``` In production, all diagnostics channel messages are automatically forwarded to [Tail Workers](https://developers.cloudflare.com/workers/observability/logs/tail-workers/) — no subscription code needed in the agent itself: * [ JavaScript ](#tab-panel-350) * [ TypeScript ](#tab-panel-351) JavaScript ``` export default { async tail(events) { for (const event of events) { for (const msg of event.diagnosticsChannelEvents) { // msg.channel is "agents:rpc", "agents:workflow", etc. console.log(msg.timestamp, msg.channel, msg.message); } } }, }; ``` TypeScript ``` export default { async tail(events) { for (const event of events) { for (const msg of event.diagnosticsChannelEvents) { // msg.channel is "agents:rpc", "agents:workflow", etc. console.log(msg.timestamp, msg.channel, msg.message); } } }, }; ``` The custom `Observability` override interface is still supported for users who need to filter or forward events to external services. For the full event reference, refer to the [Observability documentation](https://developers.cloudflare.com/agents/api-reference/observability/). #### `keepAlive()` and `keepAliveWhile()` Durable Objects are evicted after a period of inactivity (typically 70-140 seconds with no incoming requests, WebSocket messages, or alarms). During long-running operations — streaming LLM responses, waiting on external APIs, running multi-step computations — the agent can be evicted mid-flight. `keepAlive()` prevents this by creating a 30-second heartbeat schedule. The alarm firing resets the inactivity timer. Returns a disposer function that cancels the heartbeat when called. * [ JavaScript ](#tab-panel-348) * [ TypeScript ](#tab-panel-349) JavaScript ``` const dispose = await this.keepAlive(); try { const result = await longRunningComputation(); await sendResults(result); } finally { dispose(); } ``` TypeScript ``` const dispose = await this.keepAlive(); try { const result = await longRunningComputation(); await sendResults(result); } finally { dispose(); } ``` `keepAliveWhile()` wraps an async function with automatic cleanup — the heartbeat starts before the function runs and stops when it completes: * [ JavaScript ](#tab-panel-346) * [ TypeScript ](#tab-panel-347) JavaScript ``` const result = await this.keepAliveWhile(async () => { const data = await longRunningComputation(); return data; }); ``` TypeScript ``` const result = await this.keepAliveWhile(async () => { const data = await longRunningComputation(); return data; }); ``` Key details: * **Multiple concurrent callers** — Each `keepAlive()` call returns an independent disposer. Disposing one does not affect others. * **AIChatAgent built-in** — `AIChatAgent` automatically calls `keepAlive()` during streaming responses. You do not need to add it yourself. * **Uses the scheduling system** — The heartbeat does not conflict with your own schedules. It shows up in `getSchedules()` if you need to inspect it. Note `keepAlive()` is marked `@experimental` and may change between releases. For the full API reference and when-to-use guidance, refer to [Schedule tasks — Keeping the agent alive](https://developers.cloudflare.com/agents/api-reference/schedule-tasks/#keeping-the-agent-alive). #### `waitForMcpConnections` `AIChatAgent` now waits for MCP server connections to settle before calling `onChatMessage`. This ensures `this.mcp.getAITools()` returns the full set of tools, especially after Durable Object hibernation when connections are being restored in the background. * [ JavaScript ](#tab-panel-356) * [ TypeScript ](#tab-panel-357) JavaScript ``` export class ChatAgent extends AIChatAgent { // Default — waits up to 10 seconds // waitForMcpConnections = { timeout: 10_000 }; // Wait forever waitForMcpConnections = true; // Disable waiting waitForMcpConnections = false; } ``` TypeScript ``` export class ChatAgent extends AIChatAgent { // Default — waits up to 10 seconds // waitForMcpConnections = { timeout: 10_000 }; // Wait forever waitForMcpConnections = true; // Disable waiting waitForMcpConnections = false; } ``` | Value | Behavior | | -------------------- | --------------------------------------------- | | { timeout: 10\_000 } | Wait up to 10 seconds (default) | | { timeout: N } | Wait up to N milliseconds | | true | Wait indefinitely until all connections ready | | false | Do not wait (old behavior before 0.2.0) | For lower-level control, call `this.mcp.waitForConnections()` directly inside `onChatMessage` instead. #### Other improvements * **MCP deduplication by name and URL** — `addMcpServer` with HTTP transport now deduplicates on both server name and URL. Calling it with the same name but a different URL creates a new connection. URLs are normalized before comparison (trailing slashes, default ports, hostname case). * **`callbackHost` optional for non-OAuth servers** — `addMcpServer` no longer requires `callbackHost` when connecting to MCP servers that do not use OAuth. * **MCP URL security** — Server URLs are validated before connection to prevent SSRF. Private IP ranges, loopback addresses, link-local addresses, and cloud metadata endpoints are blocked. * **Custom denial messages** — `addToolOutput` now supports `state: "output-error"` with `errorText` for custom denial messages in human-in-the-loop tool approval flows. * **`requestId` in chat options** — `onChatMessage` options now include a `requestId` for logging and correlating events. #### Upgrade To update to the latest version: Terminal window ``` npm i agents@latest @cloudflare/ai-chat@latest ``` Feb 25, 2026 1. ### [Agents SDK v0.6.0: RPC transport for MCP, optional OAuth, hardened schema conversion, and @cloudflare/ai-chat fixes](https://developers.cloudflare.com/changelog/post/2026-02-25-agents-sdk-v060/) [ Agents ](https://developers.cloudflare.com/agents/)[ Workers ](https://developers.cloudflare.com/workers/) The latest release of the [Agents SDK ↗](https://github.com/cloudflare/agents) lets you define an Agent and an McpAgent in the same Worker and connect them over RPC — no HTTP, no network overhead. It also makes OAuth opt-in for simple MCP connections, hardens the schema converter for production workloads, and ships a batch of `@cloudflare/ai-chat` reliability fixes. #### RPC transport for MCP You can now connect an Agent to an McpAgent in the same Worker using a Durable Object binding instead of an HTTP URL. The connection stays entirely within the Cloudflare runtime — no network round-trips, no serialization overhead. Pass the Durable Object namespace directly to `addMcpServer`: * [ JavaScript ](#tab-panel-358) * [ TypeScript ](#tab-panel-359) JavaScript ``` import { Agent } from "agents"; export class MyAgent extends Agent { async onStart() { // Connect via DO binding — no HTTP, no network overhead await this.addMcpServer("counter", env.MY_MCP); // With props for per-user context await this.addMcpServer("counter", env.MY_MCP, { props: { userId: "user-123", role: "admin" }, }); } } ``` TypeScript ``` import { Agent } from "agents"; export class MyAgent extends Agent { async onStart() { // Connect via DO binding — no HTTP, no network overhead await this.addMcpServer("counter", env.MY_MCP); // With props for per-user context await this.addMcpServer("counter", env.MY_MCP, { props: { userId: "user-123", role: "admin" }, }); } } ``` The `addMcpServer` method now accepts `string | DurableObjectNamespace` as the second parameter with full TypeScript overloads, so HTTP and RPC paths are type-safe and cannot be mixed. Key capabilities: * **Hibernation support** — RPC connections survive Durable Object hibernation automatically. The binding name and props are persisted to storage and restored on wake-up, matching the behavior of HTTP MCP connections. * **Deduplication** — Calling `addMcpServer` with the same server name returns the existing connection instead of creating duplicates. Connection IDs are stable across hibernation restore. * **Smaller surface area** — The RPC transport internals have been rewritten and reduced from 609 lines to 245 lines. `RPCServerTransport` now uses `JSONRPCMessageSchema` from the MCP SDK for validation instead of hand-written checks. Note RPC transport is experimental. The API may change based on feedback. Refer to [the tracking issue ↗](https://github.com/cloudflare/agents/issues/565) for updates. #### Optional OAuth for MCP connections `addMcpServer()` no longer eagerly creates an OAuth provider for every connection. For servers that do not require authentication, a simple call is all you need: * [ JavaScript ](#tab-panel-352) * [ TypeScript ](#tab-panel-353) JavaScript ``` // No callbackHost, no OAuth config — just works await this.addMcpServer("my-server", "https://mcp.example.com"); ``` TypeScript ``` // No callbackHost, no OAuth config — just works await this.addMcpServer("my-server", "https://mcp.example.com"); ``` If the server responds with a 401, the SDK throws a clear error: `"This MCP server requires OAuth authentication. Provide callbackHost in addMcpServer options to enable the OAuth flow."` The restore-from-storage flow also handles missing callback URLs gracefully, skipping auth provider creation for non-OAuth servers. #### Hardened JSON Schema to TypeScript converter The schema converter used by `generateTypes()` and `getAITools()` now handles edge cases that previously caused crashes in production: * **Depth and circular reference guards** — Prevents stack overflows on recursive or deeply nested schemas * **`$ref` resolution** — Supports internal JSON Pointers (`#/definitions/...`, `#/$defs/...`, `#`) * **Tuple support** — `prefixItems` (JSON Schema 2020-12) and array `items` (draft-07) * **OpenAPI 3.0 `nullable: true`** — Supported across all schema branches * **Per-tool error isolation** — One malformed schema cannot crash the full pipeline in `generateTypes()` or `getAITools()` * **Missing `inputSchema` fallback** — `getAITools()` falls back to `{ type: "object" }` instead of throwing #### `@cloudflare/ai-chat` fixes * **Tool denial flow** — Denied tool approvals (`approved: false`) now transition to `output-denied` with a `tool_result`, fixing Anthropic provider compatibility. Custom denial messages are supported via `state: "output-error"` and `errorText`. * **Abort/cancel support** — Streaming responses now properly cancel the reader loop when the abort signal fires and send a done signal to the client. * **Duplicate message persistence** — `persistMessages()` now reconciles assistant messages by content and order, preventing duplicate rows when clients resend full history. * **`requestId` in `OnChatMessageOptions`** — Handlers can now send properly-tagged error responses for pre-stream failures. * **`redacted_thinking` preservation** — The message sanitizer no longer strips Anthropic `redacted_thinking` blocks. * **`/get-messages` reliability** — Endpoint handling moved from a prototype `onRequest()` override to a constructor wrapper, so it works even when users override `onRequest` without calling `super.onRequest()`. * **Client tool APIs undeprecated** — `createToolsFromClientSchemas`, `clientTools`, `AITool`, `extractClientToolSchemas`, and the `tools` option on `useAgentChat` are restored for SDK use cases where tools are defined dynamically at runtime. * **`jsonSchema` initialization** — Fixed `jsonSchema not initialized` error when calling `getAITools()` in `onChatMessage`. #### Upgrade To update to the latest version: Terminal window ``` npm i agents@latest @cloudflare/ai-chat@latest ``` Feb 23, 2026 1. ### [Backup and restore API for Sandbox SDK](https://developers.cloudflare.com/changelog/post/2026-02-23-sandbox-backup-restore-api/) [ Agents ](https://developers.cloudflare.com/agents/)[ R2 ](https://developers.cloudflare.com/r2/)[ Containers ](https://developers.cloudflare.com/containers/) [Sandboxes](https://developers.cloudflare.com/sandbox/) now support `createBackup()` and `restoreBackup()` methods for creating and restoring point-in-time snapshots of directories. This allows you to restore environments quickly. For instance, in order to develop in a sandbox, you may need to include a user's codebase and run a build step. Unfortunately `git clone` and `npm install` can take minutes, and you don't want to run these steps every time the user starts their sandbox. Now, after the initial setup, you can just call `createBackup()`, then `restoreBackup()` the next time this environment is needed. This makes it practical to pick up exactly where a user left off, even after days of inactivity, without repeating expensive setup steps. TypeScript ``` const sandbox = getSandbox(env.Sandbox, "my-sandbox"); // Make non-trivial changes to the file system await sandbox.gitCheckout(endUserRepo, { targetDir: "/workspace" }); await sandbox.exec("npm install", { cwd: "/workspace" }); // Create a point-in-time backup of the directory const backup = await sandbox.createBackup({ dir: "/workspace" }); // Store the handle for later use await env.KV.put(`backup:${userId}`, JSON.stringify(backup)); // ... in a future session... // Restore instead of re-cloning and reinstalling await sandbox.restoreBackup(backup); ``` Backups are stored in [R2](https://developers.cloudflare.com/r2) and can take advantage of [R2 object lifecycle rules](https://developers.cloudflare.com/sandbox/guides/backup-restore/#configure-r2-lifecycle-rules-for-automatic-cleanup) to ensure they do not persist forever. Key capabilities: * **Persist and reuse across sandbox sessions** — Easily store backup handles in KV, D1, or Durable Object storage for use in subsequent sessions * **Usable across multiple instances** — Fork a backup across many sandboxes for parallel work * **Named backups** — Provide optional human-readable labels for easier management * **TTLs** — Set time-to-live durations so backups are automatically removed from storage once they are no longer neeeded Note Backup and restore currently uses a FUSE overlay. Soon, native snapshotting at a lower level will be added to Containers and Sandboxes, improving speed and ergonomics. The current backup functionality provides a significant speed improvement over manually recreating a file system, but it will be further optimized in the future. The new snapshotting system will use a similar API, so changing to this system will be simple once it is available. To get started, refer to the [backup and restore guide](https://developers.cloudflare.com/sandbox/guides/backup-restore/) for setup instructions and usage patterns, or the [Backups API reference](https://developers.cloudflare.com/sandbox/api/backups/) for full method documentation. Feb 20, 2026 1. ### [@cloudflare/codemode v0.1.0: a new runtime agnostic modular architecture](https://developers.cloudflare.com/changelog/post/2026-02-20-codemode-sdk-rewrite/) [ Agents ](https://developers.cloudflare.com/agents/)[ Workers ](https://developers.cloudflare.com/workers/) The [@cloudflare/codemode ↗](https://www.npmjs.com/package/@cloudflare/codemode) package has been rewritten into a modular, runtime-agnostic SDK. [Code Mode ↗](https://blog.cloudflare.com/code-mode/) enables LLMs to write and execute code that orchestrates your tools, instead of calling them one at a time. This can (and does) yield significant token savings, reduces context window pressure and improves overall model performance on a task. The new `Executor` interface is runtime agnostic and comes with a prebuilt `DynamicWorkerExecutor` to run generated code in a [Dynamic Worker Loader](https://developers.cloudflare.com/workers/runtime-apis/bindings/worker-loader/). #### Breaking changes * Removed `experimental_codemode()` and `CodeModeProxy` — the package no longer owns an LLM call or model choice * New import path: `createCodeTool()` is now exported from `@cloudflare/codemode/ai` #### New features * **`createCodeTool()`** — Returns a standard AI SDK `Tool` to use in your AI agents. * **`Executor` interface** — Minimal `execute(code, fns)` contract. Implement for any code sandboxing primitive or runtime. #### `DynamicWorkerExecutor` Runs code in a [Dynamic Worker](https://developers.cloudflare.com/workers/runtime-apis/bindings/worker-loader/). It comes with the following features: * **Network isolation** — `fetch()` and `connect()` blocked by default (`globalOutbound: null`) when using `DynamicWorkerExecutor` * **Console capture** — `console.log/warn/error` captured and returned in `ExecuteResult.logs` * **Execution timeout** — Configurable via `timeout` option (default 30s) #### Usage * [ JavaScript ](#tab-panel-362) * [ TypeScript ](#tab-panel-363) JavaScript ``` import { createCodeTool } from "@cloudflare/codemode/ai"; import { DynamicWorkerExecutor } from "@cloudflare/codemode"; import { streamText } from "ai"; const executor = new DynamicWorkerExecutor({ loader: env.LOADER }); const codemode = createCodeTool({ tools: myTools, executor }); const result = streamText({ model, tools: { codemode }, messages, }); ``` TypeScript ``` import { createCodeTool } from "@cloudflare/codemode/ai"; import { DynamicWorkerExecutor } from "@cloudflare/codemode"; import { streamText } from "ai"; const executor = new DynamicWorkerExecutor({ loader: env.LOADER }); const codemode = createCodeTool({ tools: myTools, executor }); const result = streamText({ model, tools: { codemode }, messages, }); ``` #### Wrangler configuration * [ wrangler.jsonc ](#tab-panel-322) * [ wrangler.toml ](#tab-panel-323) JSONC ``` { "worker_loaders": [{ "binding": "LOADER" }], } ``` TOML ``` [[worker_loaders]] binding = "LOADER" ``` See the [Code Mode documentation](https://developers.cloudflare.com/agents/api-reference/codemode/) for full API reference and examples. #### Upgrade Terminal window ``` npm i @cloudflare/codemode@latest ``` Feb 17, 2026 1. ### [Agents SDK v0.5.0: Protocol message control, retry utilities, data parts, and @cloudflare/ai-chat v0.1.0](https://developers.cloudflare.com/changelog/post/2026-02-17-agents-sdk-v050/) [ Agents ](https://developers.cloudflare.com/agents/)[ Workers ](https://developers.cloudflare.com/workers/) The latest release of the [Agents SDK ↗](https://github.com/cloudflare/agents) adds built-in retry utilities, per-connection protocol message control, and a fully rewritten `@cloudflare/ai-chat` with data parts, tool approval persistence, and zero breaking changes. #### Retry utilities A new `this.retry()` method lets you retry any async operation with exponential backoff and jitter. You can pass an optional `shouldRetry` predicate to bail early on non-retryable errors. * [ JavaScript ](#tab-panel-360) * [ TypeScript ](#tab-panel-361) JavaScript ``` class MyAgent extends Agent { async onRequest(request) { const data = await this.retry(() => callUnreliableService(), { maxAttempts: 4, shouldRetry: (err) => !(err instanceof PermanentError), }); return Response.json(data); } } ``` TypeScript ``` class MyAgent extends Agent { async onRequest(request: Request) { const data = await this.retry(() => callUnreliableService(), { maxAttempts: 4, shouldRetry: (err) => !(err instanceof PermanentError), }); return Response.json(data); } } ``` Retry options are also available per-task on `queue()`, `schedule()`, `scheduleEvery()`, and `addMcpServer()`: * [ JavaScript ](#tab-panel-374) * [ TypeScript ](#tab-panel-375) JavaScript ``` // Per-task retry configuration, persisted in SQLite alongside the task await this.schedule( Date.now() + 60_000, "sendReport", { userId: "abc" }, { retry: { maxAttempts: 5 }, }, ); // Class-level retry defaults class MyAgent extends Agent { static options = { retry: { maxAttempts: 3 }, }; } ``` TypeScript ``` // Per-task retry configuration, persisted in SQLite alongside the task await this.schedule(Date.now() + 60_000, "sendReport", { userId: "abc" }, { retry: { maxAttempts: 5 }, }); // Class-level retry defaults class MyAgent extends Agent { static options = { retry: { maxAttempts: 3 }, }; } ``` Retry options are validated eagerly at enqueue/schedule time, and invalid values throw immediately. Internal retries have also been added for workflow operations (`terminateWorkflow`, `pauseWorkflow`, and others) with Durable Object-aware error detection. #### Per-connection protocol message control Agents automatically send JSON text frames (identity, state, MCP server lists) to every WebSocket connection. You can now suppress these per-connection for clients that cannot handle them — binary-only devices, MQTT clients, or lightweight embedded systems. * [ JavaScript ](#tab-panel-364) * [ TypeScript ](#tab-panel-365) JavaScript ``` class MyAgent extends Agent { shouldSendProtocolMessages(connection, ctx) { // Suppress protocol messages for MQTT clients const subprotocol = ctx.request.headers.get("Sec-WebSocket-Protocol"); return subprotocol !== "mqtt"; } } ``` TypeScript ``` class MyAgent extends Agent { shouldSendProtocolMessages(connection: Connection, ctx: ConnectionContext) { // Suppress protocol messages for MQTT clients const subprotocol = ctx.request.headers.get("Sec-WebSocket-Protocol"); return subprotocol !== "mqtt"; } } ``` Connections with protocol messages disabled still fully participate in RPC and regular messaging. Use `isConnectionProtocolEnabled(connection)` to check a connection's status at any time. The flag persists across Durable Object hibernation. See [Protocol messages](https://developers.cloudflare.com/agents/api-reference/protocol-messages/) for full documentation. #### `@cloudflare/ai-chat` v0.1.0 The first stable release of `@cloudflare/ai-chat` ships alongside this release with a major refactor of `AIChatAgent` internals — new `ResumableStream` class, WebSocket `ChatTransport`, and simplified SSE parsing — with zero breaking changes. Existing code using `AIChatAgent` and `useAgentChat` works as-is. Key new features: * **Data parts** — Attach typed JSON blobs (`data-*`) to messages alongside text. Supports reconciliation (type+id updates in-place), append, and transient parts (ephemeral via `onData` callback). See [Data parts](https://developers.cloudflare.com/agents/api-reference/chat-agents/#data-parts). * **Tool approval persistence** — The `needsApproval` approval UI now survives page refresh and DO hibernation. The streaming message is persisted to SQLite when a tool enters `approval-requested` state. * **`maxPersistedMessages`** — Cap SQLite message storage with automatic oldest-message deletion. * **`body` option on `useAgentChat`** — Send custom data with every request (static or dynamic). * **Incremental persistence** — Hash-based cache to skip redundant SQL writes. * **Row size guard** — Automatic two-pass compaction when messages approach the SQLite 2 MB limit. * **`autoContinueAfterToolResult` defaults to `true`** — Client-side tool results and tool approvals now automatically trigger a server continuation, matching server-executed tool behavior. Set `autoContinueAfterToolResult: false` in `useAgentChat` to restore the previous behavior. Notable bug fixes: * Resolved stream resumption race conditions * Resolved an issue where `setMessages` functional updater sent empty arrays * Resolved an issue where client tool schemas were lost after DO hibernation * Resolved `InvalidPromptError` after tool approval (`approval.id` was dropped) * Resolved an issue where message metadata was not propagated on broadcast/resume paths * Resolved an issue where `clearAll()` did not clear in-memory chunk buffers * Resolved an issue where `reasoning-delta` silently dropped data when `reasoning-start` was missed during stream resumption #### Synchronous queue and schedule getters `getQueue()`, `getQueues()`, `getSchedule()`, `dequeue()`, `dequeueAll()`, and `dequeueAllByCallback()` were unnecessarily `async` despite only performing synchronous SQL operations. They now return values directly instead of wrapping them in Promises. This is backward compatible — existing code using `await` on these methods will continue to work. #### Other improvements * **Fix TypeScript "excessively deep" error** — A depth counter on `CanSerialize` and `IsSerializableParam` types bails out to `true` after 10 levels of recursion, preventing the "Type instantiation is excessively deep" error with deeply nested types like AI SDK `CoreMessage[]`. * **POST SSE keepalive** — The POST SSE handler now sends `event: ping` every 30 seconds to keep the connection alive, matching the existing GET SSE handler behavior. This prevents POST response streams from being silently dropped by proxies during long-running tool calls. * **Widened peer dependency ranges** — Peer dependency ranges across packages have been widened to prevent cascading major bumps during 0.x minor releases. `@cloudflare/ai-chat` and `@cloudflare/codemode` are now marked as optional peer dependencies. #### Upgrade To update to the latest version: Terminal window ``` npm i agents@latest @cloudflare/ai-chat@latest ``` Feb 13, 2026 1. ### [Introducing GLM-4.7-Flash on Workers AI, @cloudflare/tanstack-ai, and workers-ai-provider v3.1.1](https://developers.cloudflare.com/changelog/post/2026-02-13-glm-47-flash-workers-ai/) [ Workers ](https://developers.cloudflare.com/workers/)[ Agents ](https://developers.cloudflare.com/agents/)[ Workers AI ](https://developers.cloudflare.com/workers-ai/) We're excited to announce **GLM-4.7-Flash** on Workers AI, a fast and efficient text generation model optimized for multilingual dialogue and instruction-following tasks, along with the brand-new [**@cloudflare/tanstack-ai** ↗](https://www.npmjs.com/package/@cloudflare/tanstack-ai) package and [**workers-ai-provider v3.1.1** ↗](https://www.npmjs.com/package/workers-ai-provider). You can now run AI agents entirely on Cloudflare. With GLM-4.7-Flash's multi-turn tool calling support, plus full compatibility with TanStack AI and the Vercel AI SDK, you have everything you need to build agentic applications that run completely at the edge. #### GLM-4.7-Flash — Multilingual Text Generation Model [@cf/zai-org/glm-4.7-flash](https://developers.cloudflare.com/workers-ai/models/glm-4.7-flash/) is a multilingual model with a 131,072 token context window, making it ideal for long-form content generation, complex reasoning tasks, and multilingual applications. **Key Features and Use Cases:** * **Multi-turn Tool Calling for Agents**: Build AI agents that can call functions and tools across multiple conversation turns * **Multilingual Support**: Built to handle content generation in multiple languages effectively * **Large Context Window**: 131,072 tokens for long-form writing, complex reasoning, and processing long documents * **Fast Inference**: Optimized for low-latency responses in chatbots and virtual assistants * **Instruction Following**: Excellent at following complex instructions for code generation and structured tasks Use GLM-4.7-Flash through the [Workers AI binding](https://developers.cloudflare.com/workers-ai/configuration/bindings/) (`env.AI.run()`), the REST API at `/run` or `/v1/chat/completions`, [AI Gateway](https://developers.cloudflare.com/ai-gateway/), or via [workers-ai-provider](https://developers.cloudflare.com/workers-ai/configuration/ai-sdk/) for the Vercel AI SDK. Pricing is available on the [model page](https://developers.cloudflare.com/workers-ai/models/glm-4.7-flash/) or [pricing page](https://developers.cloudflare.com/workers-ai/platform/pricing/). #### @cloudflare/tanstack-ai v0.1.1 — TanStack AI adapters for Workers AI and AI Gateway We've released `@cloudflare/tanstack-ai`, a new package that brings Workers AI and AI Gateway support to [TanStack AI ↗](https://tanstack.com/ai). This provides a framework-agnostic alternative for developers who prefer TanStack's approach to building AI applications. **Workers AI adapters** support four configuration modes — plain binding (`env.AI`), plain REST, AI Gateway binding (`env.AI.gateway(id)`), and AI Gateway REST — across all capabilities: * **Chat** (`createWorkersAiChat`) — Streaming chat completions with tool calling, structured output, and reasoning text streaming. * **Image generation** (`createWorkersAiImage`) — Text-to-image models. * **Transcription** (`createWorkersAiTranscription`) — Speech-to-text. * **Text-to-speech** (`createWorkersAiTts`) — Audio generation. * **Summarization** (`createWorkersAiSummarize`) — Text summarization. **AI Gateway adapters** route requests from third-party providers — OpenAI, Anthropic, Gemini, Grok, and OpenRouter — through Cloudflare AI Gateway for caching, rate limiting, and unified billing. To get started: Terminal window ``` npm install @cloudflare/tanstack-ai @tanstack/ai ``` #### workers-ai-provider v3.1.1 — transcription, speech, reranking, and reliability The Workers AI provider for the [Vercel AI SDK ↗](https://ai-sdk.dev) now supports three new capabilities beyond chat and image generation: * **Transcription** (`provider.transcription(model)`) — Speech-to-text with automatic handling of model-specific input formats across binding and REST paths. * **Text-to-speech** (`provider.speech(model)`) — Audio generation with support for voice and speed options. * **Reranking** (`provider.reranking(model)`) — Document reranking for RAG pipelines and search result ordering. TypeScript ``` import { createWorkersAI } from "workers-ai-provider"; import { experimental_transcribe, experimental_generateSpeech, rerank, } from "ai"; const workersai = createWorkersAI({ binding: env.AI }); const transcript = await experimental_transcribe({ model: workersai.transcription("@cf/openai/whisper-large-v3-turbo"), audio: audioData, mediaType: "audio/wav", }); const speech = await experimental_generateSpeech({ model: workersai.speech("@cf/deepgram/aura-1"), text: "Hello world", voice: "asteria", }); const ranked = await rerank({ model: workersai.reranking("@cf/baai/bge-reranker-base"), query: "What is machine learning?", documents: ["ML is a branch of AI.", "The weather is sunny."], }); ``` This release also includes a comprehensive reliability overhaul (v3.0.5): * **Fixed streaming** — Responses now stream token-by-token instead of buffering all chunks, using a proper `TransformStream` pipeline with backpressure. * **Fixed tool calling** — Resolved issues with tool call ID sanitization, conversation history preservation, and a heuristic that silently fell back to non-streaming mode when tools were defined. * **Premature stream termination detection** — Streams that end unexpectedly now report `finishReason: "error"` instead of silently reporting `"stop"`. * **AI Search support** — Added `createAISearch` as the canonical export (renamed from AutoRAG). `createAutoRAG` still works with a deprecation warning. To upgrade: Terminal window ``` npm install workers-ai-provider@latest ai ``` #### Resources * [@cloudflare/tanstack-ai on npm ↗](https://www.npmjs.com/package/@cloudflare/tanstack-ai) * [workers-ai-provider on npm ↗](https://www.npmjs.com/package/workers-ai-provider) * [GitHub repository ↗](https://github.com/cloudflare/ai) Feb 09, 2026 1. ### [Agents SDK v0.4.0: Readonly connections, MCP security improvements, x402 v2 migration, and custom MCP OAuth providers](https://developers.cloudflare.com/changelog/post/2026-02-09-agents-sdk-v040/) [ Agents ](https://developers.cloudflare.com/agents/)[ Workers ](https://developers.cloudflare.com/workers/) The latest release of the [Agents SDK ↗](https://github.com/cloudflare/agents) brings readonly connections, MCP protocol and security improvements, x402 payment protocol v2 migration, and the ability to customize OAuth for MCP server connections. #### Readonly connections Agents can now restrict WebSocket clients to read-only access, preventing them from modifying agent state. This is useful for dashboards, spectator views, or any scenario where clients should observe but not mutate. New hooks: `shouldConnectionBeReadonly`, `setConnectionReadonly`, `isConnectionReadonly`. Readonly connections block both client-side `setState()` and mutating `@callable()` methods, and the readonly flag survives hibernation. * [ JavaScript ](#tab-panel-366) * [ TypeScript ](#tab-panel-367) JavaScript ``` class MyAgent extends Agent { shouldConnectionBeReadonly(connection) { // Make spectators readonly return connection.url.includes("spectator"); } } ``` TypeScript ``` class MyAgent extends Agent { shouldConnectionBeReadonly(connection) { // Make spectators readonly return connection.url.includes("spectator"); } } ``` #### Custom MCP OAuth providers The new `createMcpOAuthProvider` method on the `Agent` class allows subclasses to override the default OAuth provider used when connecting to MCP servers. This enables custom authentication strategies such as pre-registered client credentials or mTLS, beyond the built-in dynamic client registration. * [ JavaScript ](#tab-panel-370) * [ TypeScript ](#tab-panel-371) JavaScript ``` class MyAgent extends Agent { createMcpOAuthProvider(callbackUrl) { return new MyCustomOAuthProvider(this.ctx.storage, this.name, callbackUrl); } } ``` TypeScript ``` class MyAgent extends Agent { createMcpOAuthProvider(callbackUrl: string): AgentMcpOAuthProvider { return new MyCustomOAuthProvider(this.ctx.storage, this.name, callbackUrl); } } ``` #### MCP SDK upgrade to 1.26.0 Upgraded the MCP SDK to 1.26.0 to prevent cross-client response leakage. Stateless MCP Servers should now create a new `McpServer` instance per request instead of sharing a single instance. A guard is added in this version of the MCP SDK which will prevent connection to a Server instance that has already been connected to a transport. Developers will need to modify their code if they declare their `McpServer` instance as a global variable. #### MCP OAuth callback URL security fix Added `callbackPath` option to `addMcpServer` to prevent instance name leakage in MCP OAuth callback URLs. When `sendIdentityOnConnect` is `false`, `callbackPath` is now required — the default callback URL would expose the instance name, undermining the security intent. Also fixes callback request detection to match via the `state` parameter instead of a loose `/callback` URL substring check, enabling custom callback paths. #### Deprecate `onStateUpdate` in favor of `onStateChanged` `onStateChanged` is a drop-in rename of `onStateUpdate` (same signature, same behavior). `onStateUpdate` still works but emits a one-time console warning per class. `validateStateChange` rejections now propagate a `CF_AGENT_STATE_ERROR` message back to the client. #### x402 v2 migration Migrated the x402 MCP payment integration from the legacy `x402` package to `@x402/core` and `@x402/evm` v2. **Breaking changes for x402 users:** * Peer dependencies changed: replace `x402` with `@x402/core` and `@x402/evm` * `PaymentRequirements` type now uses v2 fields (e.g. `amount` instead of `maxAmountRequired`) * `X402ClientConfig.account` type changed from `viem.Account` to `ClientEvmSigner` (structurally compatible with `privateKeyToAccount()`) Terminal window ``` npm uninstall x402 npm install @x402/core @x402/evm ``` Network identifiers now accept both legacy names and CAIP-2 format: TypeScript ``` // Legacy name (auto-converted) { network: "base-sepolia", } // CAIP-2 format (preferred) { network: "eip155:84532", } ``` **Other x402 changes:** * `X402ClientConfig.network` is now optional — the client auto-selects from available payment requirements * Server-side lazy initialization: facilitator connection is deferred until the first paid tool invocation * Payment tokens support both v2 (`PAYMENT-SIGNATURE`) and v1 (`X-PAYMENT`) HTTP headers * Added `normalizeNetwork` export for converting legacy network names to CAIP-2 format * Re-exports `PaymentRequirements`, `PaymentRequired`, `Network`, `FacilitatorConfig`, and `ClientEvmSigner` from `agents/x402` #### Other improvements * Fix `useAgent` and `AgentClient` crashing when using `basePath` routing * CORS handling delegated to partyserver's native support (simpler, more reliable) * Client-side `onStateUpdateError` callback for handling rejected state updates #### Upgrade To update to the latest version: Terminal window ``` npm i agents@latest ``` Feb 09, 2026 1. ### [Interactive browser terminals in Sandboxes](https://developers.cloudflare.com/changelog/post/2026-02-09-pty-terminal-support/) [ Agents ](https://developers.cloudflare.com/agents/) The [Sandbox SDK ↗](https://github.com/cloudflare/sandbox-sdk) now supports PTY (pseudo-terminal) passthrough, enabling browser-based terminal UIs to connect to sandbox shells via WebSocket. #### `sandbox.terminal(request)` The new `terminal()` method proxies a WebSocket upgrade to the container's PTY endpoint, with output buffering for replay on reconnect. * [ JavaScript ](#tab-panel-368) * [ TypeScript ](#tab-panel-369) JavaScript ``` // Worker: proxy WebSocket to container terminal return sandbox.terminal(request, { cols: 80, rows: 24 }); ``` TypeScript ``` // Worker: proxy WebSocket to container terminal return sandbox.terminal(request, { cols: 80, rows: 24 }); ``` #### Multiple terminals per sandbox Each session can have its own terminal with an isolated working directory and environment, so users can run separate shells side-by-side in the same container. * [ JavaScript ](#tab-panel-372) * [ TypeScript ](#tab-panel-373) JavaScript ``` // Multiple isolated terminals in the same sandbox const dev = await sandbox.getSession("dev"); return dev.terminal(request); ``` TypeScript ``` // Multiple isolated terminals in the same sandbox const dev = await sandbox.getSession("dev"); return dev.terminal(request); ``` #### xterm.js addon The new `@cloudflare/sandbox/xterm` export provides a `SandboxAddon` for [xterm.js ↗](https://xtermjs.org/) with automatic reconnection (exponential backoff + jitter), buffered output replay, and resize forwarding. * [ JavaScript ](#tab-panel-376) * [ TypeScript ](#tab-panel-377) JavaScript ``` import { SandboxAddon } from "@cloudflare/sandbox/xterm"; const addon = new SandboxAddon({ getWebSocketUrl: ({ sandboxId, origin }) => `${origin}/ws/terminal?id=${sandboxId}`, onStateChange: (state, error) => updateUI(state), }); terminal.loadAddon(addon); addon.connect({ sandboxId: "my-sandbox" }); ``` TypeScript ``` import { SandboxAddon } from "@cloudflare/sandbox/xterm"; const addon = new SandboxAddon({ getWebSocketUrl: ({ sandboxId, origin }) => `${origin}/ws/terminal?id=${sandboxId}`, onStateChange: (state, error) => updateUI(state), }); terminal.loadAddon(addon); addon.connect({ sandboxId: "my-sandbox" }); ``` #### Upgrade To update to the latest version: Terminal window ``` npm i @cloudflare/sandbox@latest ``` Feb 03, 2026 1. ### [Agents SDK v0.3.7: Workflows integration, synchronous state, and scheduleEvery()](https://developers.cloudflare.com/changelog/post/2026-02-03-agents-workflows-integration/) [ Agents ](https://developers.cloudflare.com/agents/)[ Workflows ](https://developers.cloudflare.com/workflows/) The latest release of the [Agents SDK ↗](https://github.com/cloudflare/agents) brings first-class support for [Cloudflare Workflows](https://developers.cloudflare.com/workflows/), synchronous state management, and new scheduling capabilities. #### Cloudflare Workflows integration Agents excel at real-time communication and state management. Workflows excel at durable execution. Together, they enable powerful patterns where Agents handle WebSocket connections while Workflows handle long-running tasks, retries, and human-in-the-loop flows. Use the new `AgentWorkflow` class to define workflows with typed access to your Agent: * [ JavaScript ](#tab-panel-386) * [ TypeScript ](#tab-panel-387) JavaScript ``` import { AgentWorkflow } from "agents/workflows"; export class ProcessingWorkflow extends AgentWorkflow { async run(event, step) { // Call Agent methods via RPC await this.agent.updateStatus(event.payload.taskId, "processing"); // Non-durable: progress reporting to clients await this.reportProgress({ step: "process", percent: 0.5 }); this.broadcastToClients({ type: "update", taskId: event.payload.taskId }); // Durable via step: idempotent, won't repeat on retry await step.mergeAgentState({ taskProgress: 0.5 }); const result = await step.do("process", async () => { return processData(event.payload.data); }); await step.reportComplete(result); return result; } } ``` TypeScript ``` import { AgentWorkflow } from "agents/workflows"; import type { AgentWorkflowEvent, AgentWorkflowStep } from "agents/workflows"; export class ProcessingWorkflow extends AgentWorkflow { async run(event: AgentWorkflowEvent, step: AgentWorkflowStep) { // Call Agent methods via RPC await this.agent.updateStatus(event.payload.taskId, "processing"); // Non-durable: progress reporting to clients await this.reportProgress({ step: "process", percent: 0.5 }); this.broadcastToClients({ type: "update", taskId: event.payload.taskId }); // Durable via step: idempotent, won't repeat on retry await step.mergeAgentState({ taskProgress: 0.5 }); const result = await step.do("process", async () => { return processData(event.payload.data); }); await step.reportComplete(result); return result; } } ``` Start workflows from your Agent with `runWorkflow()` and handle lifecycle events: * [ JavaScript ](#tab-panel-394) * [ TypeScript ](#tab-panel-395) JavaScript ``` export class MyAgent extends Agent { async startTask(taskId, data) { const instanceId = await this.runWorkflow("PROCESSING_WORKFLOW", { taskId, data, }); return { instanceId }; } async onWorkflowProgress(workflowName, instanceId, progress) { this.broadcast(JSON.stringify({ type: "progress", progress })); } async onWorkflowComplete(workflowName, instanceId, result) { console.log(`Workflow ${instanceId} completed`); } async onWorkflowError(workflowName, instanceId, error) { console.error(`Workflow ${instanceId} failed:`, error); } } ``` TypeScript ``` export class MyAgent extends Agent { async startTask(taskId: string, data: string) { const instanceId = await this.runWorkflow("PROCESSING_WORKFLOW", { taskId, data, }); return { instanceId }; } async onWorkflowProgress( workflowName: string, instanceId: string, progress: unknown, ) { this.broadcast(JSON.stringify({ type: "progress", progress })); } async onWorkflowComplete( workflowName: string, instanceId: string, result?: unknown, ) { console.log(`Workflow ${instanceId} completed`); } async onWorkflowError( workflowName: string, instanceId: string, error: unknown, ) { console.error(`Workflow ${instanceId} failed:`, error); } } ``` Key workflow methods on your Agent: * `runWorkflow(workflowName, params, options?)` — Start a workflow with optional metadata * `getWorkflow(workflowId)` / `getWorkflows(criteria?)` — Query workflows with cursor-based pagination * `approveWorkflow(workflowId)` / `rejectWorkflow(workflowId)` — Human-in-the-loop approval flows * `pauseWorkflow()`, `resumeWorkflow()`, `terminateWorkflow()` — Workflow control #### Synchronous setState() State updates are now synchronous with a new `validateStateChange()` validation hook: * [ JavaScript ](#tab-panel-380) * [ TypeScript ](#tab-panel-381) JavaScript ``` export class MyAgent extends Agent { validateStateChange(oldState, newState) { // Return false to reject the change if (newState.count < 0) return false; // Return modified state to transform return { ...newState, lastUpdated: Date.now() }; } } ``` TypeScript ``` export class MyAgent extends Agent { validateStateChange(oldState: State, newState: State): State | false { // Return false to reject the change if (newState.count < 0) return false; // Return modified state to transform return { ...newState, lastUpdated: Date.now() }; } } ``` #### scheduleEvery() for recurring tasks The new `scheduleEvery()` method enables fixed-interval recurring tasks with built-in overlap prevention: * [ JavaScript ](#tab-panel-378) * [ TypeScript ](#tab-panel-379) JavaScript ``` // Run every 5 minutes await this.scheduleEvery("syncData", 5 * 60 * 1000, { source: "api" }); ``` TypeScript ``` // Run every 5 minutes await this.scheduleEvery("syncData", 5 * 60 * 1000, { source: "api" }); ``` #### Callable system improvements * **Client-side RPC timeout** — Set timeouts on callable method invocations * **`StreamingResponse.error(message)`** — Graceful stream error signaling * **`getCallableMethods()`** — Introspection API for discovering callable methods * **Connection close handling** — Pending calls are automatically rejected on disconnect * [ JavaScript ](#tab-panel-382) * [ TypeScript ](#tab-panel-383) JavaScript ``` await agent.call("method", [args], { timeout: 5000, stream: { onChunk, onDone, onError }, }); ``` TypeScript ``` await agent.call("method", [args], { timeout: 5000, stream: { onChunk, onDone, onError }, }); ``` #### Email and routing enhancements **Secure email reply routing** — Email replies are now secured with HMAC-SHA256 signed headers, preventing unauthorized routing of emails to agent instances. **Routing improvements:** * `basePath` option to bypass default URL construction for custom routing * Server-sent identity — Agents send `name` and `agent` type on connect * New `onIdentity` and `onIdentityChange` callbacks on the client * [ JavaScript ](#tab-panel-384) * [ TypeScript ](#tab-panel-385) JavaScript ``` const agent = useAgent({ basePath: "user", onIdentity: (name, agentType) => console.log(`Connected to ${name}`), }); ``` TypeScript ``` const agent = useAgent({ basePath: "user", onIdentity: (name, agentType) => console.log(`Connected to ${name}`), }); ``` #### Upgrade To update to the latest version: Terminal window ``` npm i agents@latest ``` For the complete Workflows API reference and patterns, see [Run Workflows](https://developers.cloudflare.com/agents/api-reference/run-workflows/). Dec 22, 2025 1. ### [Agents SDK v0.3.0, workers-ai-provider v3.0.0, and ai-gateway-provider v3.0.0 with AI SDK v6 support](https://developers.cloudflare.com/changelog/post/2025-12-22-agents-sdk-ai-sdk-v6/) [ Agents ](https://developers.cloudflare.com/agents/)[ Workers ](https://developers.cloudflare.com/workers/) We've shipped a new release for the [Agents SDK ↗](https://github.com/cloudflare/agents) v0.3.0 bringing full compatibility with [AI SDK v6 ↗](https://ai-sdk.dev/docs/introduction) and introducing the unified tool pattern, dynamic tool approval, and enhanced React hooks with improved tool handling. This release includes improved streaming and tool support, dynamic tool approval (for "human in the loop" systems), enhanced React hooks with `onToolCall` callback, improved error handling for streaming responses, and seamless migration from v5 patterns. This makes it ideal for building production AI chat interfaces with Cloudflare Workers AI models, agent workflows, human-in-the-loop systems, or any application requiring reliable tool execution and approval workflows. Additionally, we've updated **workers-ai-provider v3.0.0**, the official provider for Cloudflare Workers AI models, and **ai-gateway-provider v3.0.0**, the provider for Cloudflare AI Gateway, to be compatible with AI SDK v6. #### Agents SDK v0.3.0 #### Unified Tool Pattern AI SDK v6 introduces a unified tool pattern where all tools are defined on the server using the `tool()` function. This replaces the previous client-side `AITool` pattern. #### Server-Side Tool Definition TypeScript ``` import { tool } from "ai"; import { z } from "zod"; // Server: Define ALL tools on the server const tools = { // Server-executed tool getWeather: tool({ description: "Get weather for a city", inputSchema: z.object({ city: z.string() }), execute: async ({ city }) => fetchWeather(city) }), // Client-executed tool (no execute = client handles via onToolCall) getLocation: tool({ description: "Get user location from browser", inputSchema: z.object({}) // No execute function }), // Tool requiring approval (dynamic based on input) processPayment: tool({ description: "Process a payment", inputSchema: z.object({ amount: z.number() }), needsApproval: async ({ amount }) => amount > 100, execute: async ({ amount }) => charge(amount) }) }; ``` #### Client-Side Tool Handling TypeScript ``` // Client: Handle client-side tools via onToolCall callback import { useAgentChat } from "agents/ai-react"; const { messages, sendMessage, addToolOutput } = useAgentChat({ agent, onToolCall: async ({ toolCall, addToolOutput }) => { if (toolCall.toolName === "getLocation") { const position = await new Promise((resolve, reject) => { navigator.geolocation.getCurrentPosition(resolve, reject); }); addToolOutput({ toolCallId: toolCall.toolCallId, output: { lat: position.coords.latitude, lng: position.coords.longitude } }); } } }); ``` **Key benefits of the unified tool pattern:** * **Server-defined tools**: All tools are defined in one place on the server * **Dynamic approval**: Use `needsApproval` to conditionally require user confirmation * **Cleaner client code**: Use `onToolCall` callback instead of managing tool configs * **Type safety**: Full TypeScript support with proper tool typing #### useAgentChat(options) Creates a new chat interface with enhanced v6 capabilities. TypeScript ``` // Basic chat setup with onToolCall const { messages, sendMessage, addToolOutput } = useAgentChat({ agent, onToolCall: async ({ toolCall, addToolOutput }) => { // Handle client-side tool execution await addToolOutput({ toolCallId: toolCall.toolCallId, output: { result: "success" } }); } }); ``` #### Dynamic Tool Approval Use `needsApproval` on server tools to conditionally require user confirmation: TypeScript ``` const paymentTool = tool({ description: "Process a payment", inputSchema: z.object({ amount: z.number(), recipient: z.string() }), needsApproval: async ({ amount }) => amount > 1000, execute: async ({ amount, recipient }) => { return await processPayment(amount, recipient); } }); ``` #### Tool Confirmation Detection The `isToolUIPart` and `getToolName` functions now check both static and dynamic tool parts: TypeScript ``` import { isToolUIPart, getToolName } from "ai"; const pendingToolCallConfirmation = messages.some((m) => m.parts?.some( (part) => isToolUIPart(part) && part.state === "input-available", ), ); // Handle tool confirmation if (pendingToolCallConfirmation) { await addToolOutput({ toolCallId: part.toolCallId, output: "User approved the action" }); } ``` If you need the v5 behavior (static-only checks), use the new functions: TypeScript ``` import { isStaticToolUIPart, getStaticToolName } from "ai"; ``` #### convertToModelMessages() is now async The `convertToModelMessages()` function is now asynchronous. Update all calls to await the result: TypeScript ``` import { convertToModelMessages } from "ai"; const result = streamText({ messages: await convertToModelMessages(this.messages), model: openai("gpt-4o") }); ``` #### ModelMessage type The `CoreMessage` type has been removed. Use `ModelMessage` instead: TypeScript ``` import { convertToModelMessages, type ModelMessage } from "ai"; const modelMessages: ModelMessage[] = await convertToModelMessages(messages); ``` #### generateObject mode option removed The `mode` option for `generateObject` has been removed: TypeScript ``` // Before (v5) const result = await generateObject({ mode: "json", model, schema, prompt }); // After (v6) const result = await generateObject({ model, schema, prompt }); ``` #### Structured Output with generateText While `generateObject` and `streamObject` are still functional, the recommended approach is to use `generateText`/`streamText` with the `Output.object()` helper: TypeScript ``` import { generateText, Output, stepCountIs } from "ai"; const { output } = await generateText({ model: openai("gpt-4"), output: Output.object({ schema: z.object({ name: z.string() }) }), stopWhen: stepCountIs(2), prompt: "Generate a name" }); ``` > **Note**: When using structured output with `generateText`, you must configure multiple steps with `stopWhen` because generating the structured output is itself a step. #### workers-ai-provider v3.0.0 Seamless integration with Cloudflare Workers AI models through the updated workers-ai-provider v3.0.0 with AI SDK v6 support. #### Model Setup with Workers AI Use Cloudflare Workers AI models directly in your agent workflows: TypeScript ``` import { createWorkersAI } from "workers-ai-provider"; import { useAgentChat } from "agents/ai-react"; // Create Workers AI model (v3.0.0 - enhanced v6 internals) const model = createWorkersAI({ binding: env.AI, })("@cf/meta/llama-3.2-3b-instruct"); ``` #### Enhanced File and Image Support Workers AI models now support v6 file handling with automatic conversion: TypeScript ``` // Send images and files to Workers AI models sendMessage({ role: "user", parts: [ { type: "text", text: "Analyze this image:" }, { type: "file", data: imageBuffer, mediaType: "image/jpeg", }, ], }); // Workers AI provider automatically converts to proper format ``` #### Streaming with Workers AI Enhanced streaming support with automatic warning detection: TypeScript ``` // Streaming with Workers AI models const result = await streamText({ model: createWorkersAI({ binding: env.AI })("@cf/meta/llama-3.2-3b-instruct"), messages: await convertToModelMessages(messages), onChunk: (chunk) => { // Enhanced streaming with warning handling console.log(chunk); }, }); ``` #### ai-gateway-provider v3.0.0 The ai-gateway-provider v3.0.0 now supports AI SDK v6, enabling you to use Cloudflare AI Gateway with multiple AI providers including Anthropic, Azure, AWS Bedrock, Google Vertex, and Perplexity. #### AI Gateway Setup Use Cloudflare AI Gateway to add analytics, caching, and rate limiting to your AI applications: TypeScript ``` import { createAIGateway } from "ai-gateway-provider"; // Create AI Gateway provider (v3.0.0 - enhanced v6 internals) const model = createAIGateway({ gatewayUrl: "https://gateway.ai.cloudflare.com/v1/your-account-id/gateway", headers: { "Authorization": `Bearer ${env.AI_GATEWAY_TOKEN}` } })({ provider: "openai", model: "gpt-4o" }); ``` #### Migration from v5 #### Deprecated APIs The following APIs are deprecated in favor of the unified tool pattern: | Deprecated | Replacement | | ------------------------------------- | ------------------------------------------------ | | AITool type | Use AI SDK's tool() function on server | | extractClientToolSchemas() | Define tools on server, no client schemas needed | | createToolsFromClientSchemas() | Define tools on server with tool() | | toolsRequiringConfirmation option | Use needsApproval on server tools | | experimental\_automaticToolResolution | Use onToolCall callback | | tools option in useAgentChat | Use onToolCall for client-side execution | | addToolResult() | Use addToolOutput() | #### Breaking Changes Summary 1. **Unified Tool Pattern**: All tools must be defined on the server using `tool()` 2. **`convertToModelMessages()` is async**: Add `await` to all calls 3. **`CoreMessage` removed**: Use `ModelMessage` instead 4. **`generateObject` mode removed**: Remove `mode` option 5. **`isToolUIPart` behavior changed**: Now checks both static and dynamic tool parts #### Installation Update your dependencies to use the latest versions: Terminal window ``` npm install agents@^0.3.0 workers-ai-provider@^3.0.0 ai-gateway-provider@^3.0.0 ai@^6.0.0 @ai-sdk/react@^3.0.0 @ai-sdk/openai@^3.0.0 ``` #### Resources * [Migration Guide ↗](https://github.com/cloudflare/agents/blob/main/docs/migration-to-ai-sdk-v6.md) \- Comprehensive migration documentation from v5 to v6 * [AI SDK v6 Documentation ↗](https://ai-sdk.dev/docs/migration-guides/migration-guide-6-0) \- Official AI SDK migration guide * [AI SDK v6 Announcement ↗](https://vercel.com/blog/ai-sdk-6) \- Learn about new features in v6 * [AI SDK Documentation ↗](https://sdk.vercel.ai/docs) \- Complete AI SDK reference * [GitHub Issues ↗](https://github.com/cloudflare/agents/issues) \- Report bugs or request features #### Feedback Welcome We'd love your feedback! We're particularly interested in feedback on: * **Migration experience** \- How smooth was the upgrade from v5 to v6? * **Unified tool pattern** \- How does the new server-defined tool pattern work for you? * **Dynamic tool approval** \- Does the `needsApproval` feature meet your needs? * **AI Gateway integration** \- How well does the new provider work with your setup? Nov 26, 2025 1. ### [Agents SDK v0.2.24 with resumable streaming, MCP improvements, and schedule fixes](https://developers.cloudflare.com/changelog/post/2025-11-26-agents-resumable-streaming/) [ Agents ](https://developers.cloudflare.com/agents/)[ Workers ](https://developers.cloudflare.com/workers/) The latest release of [@cloudflare/agents ↗](https://github.com/cloudflare/agents) brings resumable streaming, significant MCP client improvements, and critical fixes for schedules and Durable Object lifecycle management. #### Resumable streaming `AIChatAgent` now supports resumable streaming, allowing clients to reconnect and continue receiving streamed responses without losing data. This is useful for: * Long-running AI responses * Users on unreliable networks * Users switching between devices mid-conversation * Background tasks where users navigate away and return * Real-time collaboration where multiple clients need to stay in sync Streams are maintained across page refreshes, broken connections, and syncing across open tabs and devices. #### Other improvements * Default JSON schema validator added to MCP client * [Schedules ↗](https://developers.cloudflare.com/agents/api-reference/schedule-tasks/) can now safely destroy the agent #### MCP client API improvements The `MCPClientManager` API has been redesigned for better clarity and control: * **New `registerServer()` method**: Register MCP servers without immediately connecting * **New `connectToServer()` method**: Establish connections to registered servers * **Improved reconnect logic**: `restoreConnectionsFromStorage()` now properly handles failed connections TypeScript ``` // Register a server to Agent const { id } = await this.mcp.registerServer({ name: "my-server", url: "https://my-mcp-server.example.com", }); // Connect when ready await this.mcp.connectToServer(id); // Discover tools, prompts and resources await this.mcp.discoverIfConnected(id); ``` The SDK now includes a formalized `MCPConnectionState` enum with states: `idle`, `connecting`, `authenticating`, `connected`, `discovering`, and `ready`. #### Enhanced MCP discovery MCP discovery fetches the available tools, prompts, and resources from an MCP server so your agent knows what capabilities are available. The `MCPClientConnection` class now includes a dedicated `discover()` method with improved reliability: * Supports cancellation via AbortController * Configurable timeout (default 15s) * Discovery failures now throw errors immediately instead of silently continuing #### Bug fixes * Fixed a bug where [schedules ↗](https://developers.cloudflare.com/agents/api-reference/schedule-tasks/) meant to fire immediately with this.schedule(0, ...) or `this.schedule(new Date(), ...)` would not fire * Fixed an issue where schedules that took longer than 30 seconds would occasionally time out * Fixed SSE transport now properly forwards session IDs and request headers * Fixed AI SDK stream events convertion to UIMessageStreamPart #### Upgrade To update to the latest version: Terminal window ``` npm i agents@latest ``` Sep 10, 2025 1. ### [Agents SDK v0.1.0 and workers-ai-provider v2.0.0 with AI SDK v5 support](https://developers.cloudflare.com/changelog/post/2025-09-03-agents-sdk-beta-v5/) [ Agents ](https://developers.cloudflare.com/agents/)[ Workers ](https://developers.cloudflare.com/workers/) We've shipped a new release for the [Agents SDK ↗](https://github.com/cloudflare/agents) bringing full compatibility with [AI SDK v5 ↗](https://ai-sdk.dev/docs/introduction) and introducing automatic message migration that handles all legacy formats transparently. This release includes improved streaming and tool support, tool confirmation detection (for "human in the loop" systems), enhanced React hooks with automatic tool resolution, improved error handling for streaming responses, and seamless migration utilities that work behind the scenes. This makes it ideal for building production AI chat interfaces with Cloudflare Workers AI models, agent workflows, human-in-the-loop systems, or any application requiring reliable message handling across SDK versions — all while maintaining backward compatibility. Additionally, we've updated workers-ai-provider v2.0.0, the official provider for Cloudflare Workers AI models, to be compatible with AI SDK v5. #### useAgentChat(options) Creates a new chat interface with enhanced v5 capabilities. TypeScript ``` // Basic chat setup const { messages, sendMessage, addToolResult } = useAgentChat({ agent, experimental_automaticToolResolution: true, tools, }); // With custom tool confirmation const chat = useAgentChat({ agent, experimental_automaticToolResolution: true, toolsRequiringConfirmation: ["dangerousOperation"], }); ``` #### Automatic Tool Resolution Tools are automatically categorized based on their configuration: TypeScript ``` const tools = { // Auto-executes (has execute function) getLocalTime: { description: "Get current local time", inputSchema: z.object({}), execute: async () => new Date().toLocaleString(), }, // Requires confirmation (no execute function) deleteFile: { description: "Delete a file from the system", inputSchema: z.object({ filename: z.string(), }), }, // Server-executed (no client confirmation) analyzeData: { description: "Analyze dataset on server", inputSchema: z.object({ data: z.array(z.number()) }), serverExecuted: true, }, } satisfies Record; ``` #### Message Handling Send messages using the new v5 format with parts array: TypeScript ``` // Text message sendMessage({ role: "user", parts: [{ type: "text", text: "Hello, assistant!" }], }); // Multi-part message with file sendMessage({ role: "user", parts: [ { type: "text", text: "Analyze this image:" }, { type: "image", image: imageData }, ], }); ``` #### Tool Confirmation Detection Simplified logic for detecting pending tool confirmations: TypeScript ``` const pendingToolCallConfirmation = messages.some((m) => m.parts?.some( (part) => isToolUIPart(part) && part.state === "input-available", ), ); // Handle tool confirmation if (pendingToolCallConfirmation) { await addToolResult({ toolCallId: part.toolCallId, tool: getToolName(part), output: "User approved the action", }); } ``` #### Automatic Message Migration Seamlessly handle legacy message formats without code changes. TypeScript ``` // All these formats are automatically converted: // Legacy v4 string content const legacyMessage = { role: "user", content: "Hello world", }; // Legacy v4 with tool calls const legacyWithTools = { role: "assistant", content: "", toolInvocations: [ { toolCallId: "123", toolName: "weather", args: { city: "SF" }, state: "result", result: "Sunny, 72°F", }, ], }; // Automatically becomes v5 format: // { // role: "assistant", // parts: [{ // type: "tool-call", // toolCallId: "123", // toolName: "weather", // args: { city: "SF" }, // state: "result", // result: "Sunny, 72°F" // }] // } ``` #### Tool Definition Updates Migrate tool definitions to use the new `inputSchema` property. TypeScript ``` // Before (AI SDK v4) const tools = { weather: { description: "Get weather information", parameters: z.object({ city: z.string(), }), execute: async (args) => { return await getWeather(args.city); }, }, }; // After (AI SDK v5) const tools = { weather: { description: "Get weather information", inputSchema: z.object({ city: z.string(), }), execute: async (args) => { return await getWeather(args.city); }, }, }; ``` #### Cloudflare Workers AI Integration Seamless integration with Cloudflare Workers AI models through the updated workers-ai-provider v2.0.0. #### Model Setup with Workers AI Use Cloudflare Workers AI models directly in your agent workflows: TypeScript ``` import { createWorkersAI } from "workers-ai-provider"; import { useAgentChat } from "agents/ai-react"; // Create Workers AI model (v2.0.0 - same API, enhanced v5 internals) const model = createWorkersAI({ binding: env.AI, })("@cf/meta/llama-3.2-3b-instruct"); ``` #### Enhanced File and Image Support Workers AI models now support v5 file handling with automatic conversion: TypeScript ``` // Send images and files to Workers AI models sendMessage({ role: "user", parts: [ { type: "text", text: "Analyze this image:" }, { type: "file", data: imageBuffer, mediaType: "image/jpeg", }, ], }); // Workers AI provider automatically converts to proper format ``` #### Streaming with Workers AI Enhanced streaming support with automatic warning detection: TypeScript ``` // Streaming with Workers AI models const result = await streamText({ model: createWorkersAI({ binding: env.AI })("@cf/meta/llama-3.2-3b-instruct"), messages, onChunk: (chunk) => { // Enhanced streaming with warning handling console.log(chunk); }, }); ``` #### Import Updates Update your imports to use the new v5 types: TypeScript ``` // Before (AI SDK v4) import type { Message } from "ai"; import { useChat } from "ai/react"; // After (AI SDK v5) import type { UIMessage } from "ai"; // or alias for compatibility import type { UIMessage as Message } from "ai"; import { useChat } from "@ai-sdk/react"; ``` #### Resources * [Migration Guide ↗](https://github.com/cloudflare/agents/blob/main/docs/migration-to-ai-sdk-v5.md) \- Comprehensive migration documentation * [AI SDK v5 Documentation ↗](https://ai-sdk.dev/docs/migration-guides/migration-guide-5-0) \- Official AI SDK migration guide * [An Example PR showing the migration from AI SDK v4 to v5 ↗](https://github.com/cloudflare/agents-starter/pull/105) * [GitHub Issues ↗](https://github.com/cloudflare/agents/issues) \- Report bugs or request features #### Feedback Welcome We'd love your feedback! We're particularly interested in feedback on: * **Migration experience** \- How smooth was the upgrade process? * **Tool confirmation workflow** \- Does the new automatic detection work as expected? * **Message format handling** \- Any edge cases with legacy message conversion? Aug 05, 2025 1. ### [Agents SDK adds MCP Elicitation support, http-streamable suppport, task queues, email integration and more](https://developers.cloudflare.com/changelog/post/2025-08-05-agents-mcp-update/) [ Agents ](https://developers.cloudflare.com/agents/)[ Workers ](https://developers.cloudflare.com/workers/) The latest releases of [@cloudflare/agents ↗](https://github.com/cloudflare/agents) brings major improvements to MCP transport protocols support and agents connectivity. Key updates include: #### MCP elicitation support MCP servers can now request user input during tool execution, enabling interactive workflows like confirmations, forms, and multi-step processes. This feature uses durable storage to preserve elicitation state even during agent hibernation, ensuring seamless user interactions across agent lifecycle events. TypeScript ``` // Request user confirmation via elicitation const confirmation = await this.elicitInput({ message: `Are you sure you want to increment the counter by ${amount}?`, requestedSchema: { type: "object", properties: { confirmed: { type: "boolean", title: "Confirm increment", description: "Check to confirm the increment", }, }, required: ["confirmed"], }, }); ``` Check out our [demo ↗](https://github.com/whoiskatrin/agents/tree/main/examples/mcp-elicitation-demo) to see elicitation in action. #### HTTP streamable transport for MCP MCP now supports HTTP streamable transport which is recommended over SSE. This transport type offers: * **Better performance**: More efficient data streaming and reduced overhead * **Improved reliability**: Enhanced connection stability and error recover- **Automatic fallback**: If streamable transport is not available, it gracefully falls back to SSE TypeScript ``` export default MyMCP.serve("/mcp", { binding: "MyMCP", }); ``` The SDK automatically selects the best available transport method, gracefully falling back from streamable-http to SSE when needed. #### Enhanced MCP connectivity Significant improvements to MCP server connections and transport reliability: * **Auto transport selection**: Automatically determines the best transport method, falling back from streamable-http to SSE as needed * **Improved error handling**: Better connection state management and error reporting for MCP servers * **Reliable prop updates**: Centralized agent property updates ensure consistency across different contexts #### Lightweight .queue for fast task deferral You can use `.queue()` to enqueue background work — ideal for tasks like processing user messages, sending notifications etc. TypeScript ``` class MyAgent extends Agent { doSomethingExpensive(payload) { // a long running process that you want to run in the background } queueSomething() { await this.queue("doSomethingExpensive", somePayload); // this will NOT block further execution, and runs in the background await this.queue("doSomethingExpensive", someOtherPayload); // the callback will NOT run until the previous callback is complete // ... call as many times as you want } } ``` Want to try it yourself? Just define a method like processMessage in your agent, and you’re ready to scale. #### New email adapter Want to build an AI agent that can receive and respond to emails automatically? With the new email adapter and onEmail lifecycle method, now you can. TypeScript ``` export class EmailAgent extends Agent { async onEmail(email: AgentEmail) { const raw = await email.getRaw(); const parsed = await PostalMime.parse(raw); // create a response based on the email contents // and then send a reply await this.replyToEmail(email, { fromName: "Email Agent", body: `Thanks for your email! You've sent us "${parsed.subject}". We'll process it shortly.`, }); } } ``` You route incoming mail like this: TypeScript ``` export default { async email(email, env) { await routeAgentEmail(email, env, { resolver: createAddressBasedEmailResolver("EmailAgent"), }); }, }; ``` You can find a full example [here ↗](https://github.com/cloudflare/agents/tree/main/examples/email-agent). #### Automatic context wrapping for custom methods Custom methods are now automatically wrapped with the agent's context, so calling `getCurrentAgent()` should work regardless of where in an agent's lifecycle it's called. Previously this would not work on RPC calls, but now just works out of the box. TypeScript ``` export class MyAgent extends Agent { async suggestReply(message) { // getCurrentAgent() now correctly works, even when called inside an RPC method const { agent } = getCurrentAgent()!; return generateText({ prompt: `Suggest a reply to: "${message}" from "${agent.name}"`, tools: [replyWithEmoji], }); } } ``` Try it out and tell us what you build! Aug 05, 2025 1. ### [Cloudflare Sandbox SDK adds streaming, code interpreter, Git support, process control and more](https://developers.cloudflare.com/changelog/post/2025-08-05-sandbox-sdk-major-update/) [ Agents ](https://developers.cloudflare.com/agents/)[ Workers ](https://developers.cloudflare.com/workers/) We’ve shipped a major release for the [@cloudflare/sandbox ↗](https://github.com/cloudflare/sandbox-sdk) SDK, turning it into a full-featured, container-based execution platform that runs securely on Cloudflare Workers. This update adds live streaming of output, persistent Python and JavaScript code interpreters with rich output support (charts, tables, HTML, JSON), file system access, Git operations, full background process control, and the ability to expose running services via public URLs. This makes it ideal for building AI agents, CI runners, cloud REPLs, data analysis pipelines, or full developer tools — all without managing infrastructure. #### Code interpreter (Python, JS, TS) Create persistent code contexts with support for rich visual + structured outputs. #### createCodeContext(options) Creates a new code execution context with persistent state. TypeScript ``` // Create a Python context const pythonCtx = await sandbox.createCodeContext({ language: "python" }); // Create a JavaScript context const jsCtx = await sandbox.createCodeContext({ language: "javascript" }); ``` Options: * language: Programming language ('python' | 'javascript' | 'typescript') * cwd: Working directory (default: /workspace) * envVars: Environment variables for the context #### runCode(code, options) Executes code with optional streaming callbacks. TypeScript ``` // Simple execution const execution = await sandbox.runCode('print("Hello World")', { context: pythonCtx, }); // With streaming callbacks await sandbox.runCode( ` for i in range(5): print(f"Step {i}") time.sleep(1) `, { context: pythonCtx, onStdout: (output) => console.log("Real-time:", output.text), onResult: (result) => console.log("Result:", result), }, ); ``` Options: * language: Programming language ('python' | 'javascript' | 'typescript') * cwd: Working directory (default: /workspace) * envVars: Environment variables for the context #### Real-time streaming output Returns a streaming response for real-time processing. TypeScript ``` const stream = await sandbox.runCodeStream( "import time; [print(i) for i in range(10)]", ); // Process the stream as needed ``` #### Rich output handling Interpreter outputs are auto-formatted and returned in multiple formats: * text * html (e.g., Pandas tables) * png, svg (e.g., Matplotlib charts) * json (structured data) * chart (parsed visualizations) TypeScript ``` const result = await sandbox.runCode( ` import seaborn as sns import matplotlib.pyplot as plt data = sns.load_dataset("flights") pivot = data.pivot("month", "year", "passengers") sns.heatmap(pivot, annot=True, fmt="d") plt.title("Flight Passengers") plt.show() pivot.to_dict() `, { context: pythonCtx }, ); if (result.png) { console.log("Chart output:", result.png); } ``` #### Preview URLs from Exposed Ports Start background processes and expose them with live URLs. TypeScript ``` await sandbox.startProcess("python -m http.server 8000"); const preview = await sandbox.exposePort(8000); console.log("Live preview at:", preview.url); ``` #### Full process lifecycle control Start, inspect, and terminate long-running background processes. TypeScript ``` const process = await sandbox.startProcess("node server.js"); console.log(`Started process ${process.id} with PID ${process.pid}`); // Monitor the process const logStream = await sandbox.streamProcessLogs(process.id); for await (const log of parseSSEStream(logStream)) { console.log(`Server: ${log.data}`); } ``` * listProcesses() - List all running processes * getProcess(id) - Get detailed process status * killProcess(id, signal) - Terminate specific processes * killAllProcesses() - Kill all processes * streamProcessLogs(id, options) - Stream logs from running processes * getProcessLogs(id) - Get accumulated process output #### Git integration Clone Git repositories directly into the sandbox. TypeScript ``` await sandbox.gitCheckout("https://github.com/user/repo", { branch: "main", targetDir: "my-project", }); ``` Sandboxes are still experimental. We're using them to explore how isolated, container-like workloads might scale on Cloudflare — and to help define the developer experience around them. Aug 05, 2025 1. ### [OpenAI open models now available on Workers AI](https://developers.cloudflare.com/changelog/post/2025-08-05-openai-open-models/) [ Agents ](https://developers.cloudflare.com/agents/)[ Workers AI ](https://developers.cloudflare.com/workers-ai/) We're thrilled to be a Day 0 partner with [OpenAI ↗](http://openai.com/index/introducing-gpt-oss) to bring their [latest open models ↗](https://openai.com/index/gpt-oss-model-card/) to Workers AI, including support for Responses API, Code Interpreter, and Web Search (coming soon). Get started with the new models at `@cf/openai/gpt-oss-120b` and `@cf/openai/gpt-oss-20b`. Check out the [blog ↗](https://blog.cloudflare.com/openai-gpt-oss-on-workers-ai) for more details about the new models, and the [gpt-oss-120b](https://developers.cloudflare.com/workers-ai/models/gpt-oss-120b) and [gpt-oss-20b](https://developers.cloudflare.com/workers-ai/models/gpt-oss-20b) model pages for more information about pricing and context windows. #### Responses API If you call the model through: * Workers Binding, it will accept/return Responses API – `env.AI.run(“@cf/openai/gpt-oss-120b”)` * REST API on `/run` endpoint, it will accept/return Responses API – `https://api.cloudflare.com/client/v4/accounts//ai/run/@cf/openai/gpt-oss-120b` * REST API on new `/responses` endpoint, it will accept/return Responses API – `https://api.cloudflare.com/client/v4/accounts//ai/v1/responses` * REST API for OpenAI Compatible endpoint, it will return Chat Completions (coming soon) – `https://api.cloudflare.com/client/v4/accounts//ai/v1/chat/completions` ``` curl https://api.cloudflare.com/client/v4/accounts//ai/v1/responses \ -H "Content-Type: application/json" \ -H "Authorization: Bearer $CLOUDFLARE_API_KEY" \ -d '{ "model": "@cf/openai/gpt-oss-120b", "reasoning": {"effort": "medium"}, "input": [ { "role": "user", "content": "What are the benefits of open-source models?" } ] }' ``` #### Code Interpreter The model is natively trained to support stateful code execution, and we've implemented support for this feature using our [Sandbox SDK ↗](https://github.com/cloudflare/sandbox-sdk) and [Containers ↗](https://blog.cloudflare.com/containers-are-available-in-public-beta-for-simple-global-and-programmable/). Cloudflare's Developer Platform is uniquely positioned to support this feature, so we're very excited to bring our products together to support this new use case. #### Web Search (coming soon) We are working to implement Web Search for the model, where users can bring their own Exa API Key so the model can browse the Internet. Jun 25, 2025 1. ### [Run AI-generated code on-demand with Code Sandboxes (new)](https://developers.cloudflare.com/changelog/post/2025-06-24-announcing-sandboxes/) [ Agents ](https://developers.cloudflare.com/agents/)[ Workers ](https://developers.cloudflare.com/workers/)[ Workflows ](https://developers.cloudflare.com/workflows/) AI is supercharging app development for everyone, but we need a safe way to run untrusted, LLM-written code. We’re introducing [Sandboxes ↗](https://www.npmjs.com/package/@cloudflare/sandbox), which let your Worker run actual processes in a secure, container-based environment. TypeScript ``` import { getSandbox } from "@cloudflare/sandbox"; export { Sandbox } from "@cloudflare/sandbox"; export default { async fetch(request: Request, env: Env) { const sandbox = getSandbox(env.Sandbox, "my-sandbox"); return sandbox.exec("ls", ["-la"]); }, }; ``` #### Methods * `exec(command: string, args: string[], options?: { stream?: boolean })`:Execute a command in the sandbox. * `gitCheckout(repoUrl: string, options: { branch?: string; targetDir?: string; stream?: boolean })`: Checkout a git repository in the sandbox. * `mkdir(path: string, options: { recursive?: boolean; stream?: boolean })`: Create a directory in the sandbox. * `writeFile(path: string, content: string, options: { encoding?: string; stream?: boolean })`: Write content to a file in the sandbox. * `readFile(path: string, options: { encoding?: string; stream?: boolean })`: Read content from a file in the sandbox. * `deleteFile(path: string, options?: { stream?: boolean })`: Delete a file from the sandbox. * `renameFile(oldPath: string, newPath: string, options?: { stream?: boolean })`: Rename a file in the sandbox. * `moveFile(sourcePath: string, destinationPath: string, options?: { stream?: boolean })`: Move a file from one location to another in the sandbox. * `ping()`: Ping the sandbox. Sandboxes are still experimental. We're using them to explore how isolated, container-like workloads might scale on Cloudflare — and to help define the developer experience around them. You can try it today from your Worker, with just a few lines of code. Let us know what you build. Apr 07, 2025 1. ### [Build MCP servers with the Agents SDK](https://developers.cloudflare.com/changelog/post/2025-04-07-mcp-servers-agents-sdk-updates/) [ Agents ](https://developers.cloudflare.com/agents/)[ Workers ](https://developers.cloudflare.com/workers/) The Agents SDK now includes built-in support for building remote MCP (Model Context Protocol) servers directly as part of your Agent. This allows you to easily create and manage MCP servers, without the need for additional infrastructure or configuration. The SDK includes a new `MCPAgent` class that extends the `Agent` class and allows you to expose resources and tools over the MCP protocol, as well as authorization and authentication to enable remote MCP servers. * [ JavaScript ](#tab-panel-392) * [ TypeScript ](#tab-panel-393) JavaScript ``` export class MyMCP extends McpAgent { server = new McpServer({ name: "Demo", version: "1.0.0", }); async init() { this.server.resource(`counter`, `mcp://resource/counter`, (uri) => { // ... }); this.server.tool( "add", "Add two numbers together", { a: z.number(), b: z.number() }, async ({ a, b }) => { // ... }, ); } } ``` TypeScript ``` export class MyMCP extends McpAgent { server = new McpServer({ name: "Demo", version: "1.0.0", }); async init() { this.server.resource(`counter`, `mcp://resource/counter`, (uri) => { // ... }); this.server.tool( "add", "Add two numbers together", { a: z.number(), b: z.number() }, async ({ a, b }) => { // ... }, ); } } ``` See [the example ↗](https://github.com/cloudflare/agents/tree/main/examples/mcp) for the full code and as the basis for building your own MCP servers, and the [client example ↗](https://github.com/cloudflare/agents/tree/main/examples/mcp-client) for how to build an Agent that acts as an MCP client. To learn more, review the [announcement blog ↗](https://blog.cloudflare.com/building-ai-agents-with-mcp-authn-authz-and-durable-objects) as part of Developer Week 2025. #### Agents SDK updates We've made a number of improvements to the [Agents SDK](https://developers.cloudflare.com/agents/), including: * Support for building MCP servers with the new `MCPAgent` class. * The ability to export the current agent, request and WebSocket connection context using `import { context } from "agents"`, allowing you to minimize or avoid direct dependency injection when calling tools. * Fixed a bug that prevented query parameters from being sent to the Agent server from the `useAgent` React hook. * Automatically converting the `agent` name in `useAgent` or `useAgentChat` to kebab-case to ensure it matches the naming convention expected by [routeAgentRequest](https://developers.cloudflare.com/agents/api-reference/routing/). To install or update the Agents SDK, run `npm i agents@latest` in an existing project, or explore the `agents-starter` project: Terminal window ``` npm create cloudflare@latest -- --template cloudflare/agents-starter ``` See the full release notes and changelog [on the Agents SDK repository ↗](https://github.com/cloudflare/agents/blob/main/packages/agents/CHANGELOG.md) and Mar 18, 2025 1. ### [npm i agents](https://developers.cloudflare.com/changelog/post/2025-03-18-npm-i-agents/) [ Agents ](https://developers.cloudflare.com/agents/)[ Workers ](https://developers.cloudflare.com/workers/) ![npm i agents](https://developers.cloudflare.com/_astro/npm-i-agents.CXCpJ1-7.apng) #### `agents-sdk` \-> `agents` Updated 📝 **We've renamed the Agents package to `agents`**! If you've already been building with the Agents SDK, you can update your dependencies to use the new package name, and replace references to `agents-sdk` with `agents`: Terminal window ``` # Install the new package npm i agents ``` Terminal window ``` # Remove the old (deprecated) package npm uninstall agents-sdk # Find instances of the old package name in your codebase grep -r 'agents-sdk' . # Replace instances of the old package name with the new one # (or use find-replace in your editor) sed -i 's/agents-sdk/agents/g' $(grep -rl 'agents-sdk' .) ``` All future updates will be pushed to the new `agents` package, and the older package has been marked as deprecated. #### Agents SDK updates New We've added a number of big new features to the Agents SDK over the past few weeks, including: * You can now set `cors: true` when using `routeAgentRequest` to return permissive default CORS headers to Agent responses. * The regular client now syncs state on the agent (just like the React version). * `useAgentChat` bug fixes for passing headers/credentials, including properly clearing cache on unmount. * Experimental `/schedule` module with a prompt/schema for adding scheduling to your app (with evals!). * Changed the internal `zod` schema to be compatible with the limitations of Google's Gemini models by removing the discriminated union, allowing you to use Gemini models with the scheduling API. We've also fixed a number of bugs with state synchronization and the React hooks. * [ JavaScript ](#tab-panel-388) * [ TypeScript ](#tab-panel-389) JavaScript ``` // via https://github.com/cloudflare/agents/tree/main/examples/cross-domain export default { async fetch(request, env) { return ( // Set { cors: true } to enable CORS headers. (await routeAgentRequest(request, env, { cors: true })) || new Response("Not found", { status: 404 }) ); }, }; ``` TypeScript ``` // via https://github.com/cloudflare/agents/tree/main/examples/cross-domain export default { async fetch(request: Request, env: Env) { return ( // Set { cors: true } to enable CORS headers. (await routeAgentRequest(request, env, { cors: true })) || new Response("Not found", { status: 404 }) ); }, } satisfies ExportedHandler; ``` #### Call Agent methods from your client code New We've added a new [@unstable\_callable()](https://developers.cloudflare.com/agents/api-reference/agents-api/) decorator for defining methods that can be called directly from clients. This allows you call methods from within your client code: you can call methods (with arguments) and get native JavaScript objects back. * [ JavaScript ](#tab-panel-390) * [ TypeScript ](#tab-panel-391) JavaScript ``` // server.ts import { unstable_callable, Agent } from "agents"; export class Rpc extends Agent { // Use the decorator to define a callable method @unstable_callable({ description: "rpc test", }) async getHistory() { return this.sql`SELECT * FROM history ORDER BY created_at DESC LIMIT 10`; } } ``` TypeScript ``` // server.ts import { unstable_callable, Agent, type StreamingResponse } from "agents"; import type { Env } from "../server"; export class Rpc extends Agent { // Use the decorator to define a callable method @unstable_callable({ description: "rpc test", }) async getHistory() { return this.sql`SELECT * FROM history ORDER BY created_at DESC LIMIT 10`; } } ``` #### agents-starter Updated We've fixed a number of small bugs in the [agents-starter ↗](https://github.com/cloudflare/agents-starter) project — a real-time, chat-based example application with tool-calling & human-in-the-loop built using the Agents SDK. The starter has also been upgraded to use the latest [wrangler v4](https://developers.cloudflare.com/changelog/2025-03-13-wrangler-v4/) release. If you're new to Agents, you can install and run the `agents-starter` project in two commands: Terminal window ``` # Install it $ npm create cloudflare@latest agents-starter -- --template="cloudflare/agents-starter" # Run it $ npm run start ``` You can use the starter as a template for your own Agents projects: open up `src/server.ts` and `src/client.tsx` to see how the Agents SDK is used. #### More documentation Updated We've heard your feedback on the Agents SDK documentation, and we're shipping more API reference material and usage examples, including: * Expanded [API reference documentation](https://developers.cloudflare.com/agents/api-reference/), covering the methods and properties exposed by the Agents SDK, as well as more usage examples. * More [Client API](https://developers.cloudflare.com/agents/api-reference/agents-api/#client-api) documentation that documents `useAgent`, `useAgentChat` and the new `@unstable_callable` RPC decorator exposed by the SDK. * New documentation on how to [route requests to agents](https://developers.cloudflare.com/agents/api-reference/routing/) and (optionally) authenticate clients before they connect to your Agents. Note that the Agents SDK is continually growing: the type definitions included in the SDK will always include the latest APIs exposed by the `agents` package. If you're still wondering what Agents are, [read our blog on building AI Agents on Cloudflare ↗](https://blog.cloudflare.com/build-ai-agents-on-cloudflare/) and/or visit the [Agents documentation](https://developers.cloudflare.com/agents/) to learn more. Feb 25, 2025 1. ### [Introducing the Agents SDK](https://developers.cloudflare.com/changelog/post/2025-02-25-agents-sdk/) [ Agents ](https://developers.cloudflare.com/agents/)[ Workers ](https://developers.cloudflare.com/workers/) We've released the [Agents SDK ↗](http://blog.cloudflare.com/build-ai-agents-on-cloudflare/), a package and set of tools that help you build and ship AI Agents. You can get up and running with a [chat-based AI Agent ↗](https://github.com/cloudflare/agents-starter) (and deploy it to Workers) that uses the Agents SDK, tool calling, and state syncing with a React-based front-end by running the following command: Terminal window ``` npm create cloudflare@latest agents-starter -- --template="cloudflare/agents-starter" # open up README.md and follow the instructions ``` You can also add an Agent to any existing Workers application by installing the `agents` package directly Terminal window ``` npm i agents ``` ... and then define your first Agent: TypeScript ``` import { Agent } from "agents"; export class YourAgent extends Agent { // Build it out // Access state on this.state or query the Agent's database via this.sql // Handle WebSocket events with onConnect and onMessage // Run tasks on a schedule with this.schedule // Call AI models // ... and/or call other Agents. } ``` Head over to the [Agents documentation](https://developers.cloudflare.com/agents/) to learn more about the Agents SDK, the SDK APIs, as well as how to test and deploying agents to production. Feb 14, 2025 1. ### [Build AI Agents with Example Prompts](https://developers.cloudflare.com/changelog/post/2025-02-14-example-ai-prompts/) [ Agents ](https://developers.cloudflare.com/agents/)[ Workers ](https://developers.cloudflare.com/workers/)[ Workflows ](https://developers.cloudflare.com/workflows/) We've added an [example prompt](https://developers.cloudflare.com/workers/get-started/prompting/) to help you get started with building AI agents and applications on Cloudflare [Workers](https://developers.cloudflare.com/workers/), including [Workflows](https://developers.cloudflare.com/workflows/), [Durable Objects](https://developers.cloudflare.com/durable-objects/), and [Workers KV](https://developers.cloudflare.com/kv/). You can use this prompt with your favorite AI model, including Claude 3.5 Sonnet, OpenAI's o3-mini, Gemini 2.0 Flash, or Llama 3.3 on Workers AI. Models with large context windows will allow you to paste the prompt directly: provide your own prompt within the `` tags. Terminal window ``` {paste_prompt_here} user: Build an AI agent using Cloudflare Workflows. The Workflow should run when a new GitHub issue is opened on a specific project with the label 'help' or 'bug', and attempt to help the user troubleshoot the issue by calling the OpenAI API with the issue title and description, and a clear, structured prompt that asks the model to suggest 1-3 possible solutions to the issue. Any code snippets should be formatted in Markdown code blocks. Documentation and sources should be referenced at the bottom of the response. The agent should then post the response to the GitHub issue. The agent should run as the provided GitHub bot account. ``` This prompt is still experimental, but we encourage you to try it out and [provide feedback ↗](https://github.com/cloudflare/cloudflare-docs/issues/new?template=content.edit.yml). [Search all changelog entries](https://developers.cloudflare.com/search/?contentType=Changelog+entry)