Changelog

New updates and improvements at Cloudflare.

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Workers

Mar 18, 2026

Manage Cloudflare Tunnels with Wrangler
Cloudflare Tunnel Workers
You can now manage Cloudflare Tunnels directly from Wrangler, the CLI for the Cloudflare Developer Platform. The new wrangler tunnel commands let you create, run, and manage tunnels without leaving your terminal.

Available commands:
- wrangler tunnel create — Create a new remotely managed tunnel.
- wrangler tunnel list — List all tunnels in your account.
- wrangler tunnel info — Display details about a specific tunnel.
- wrangler tunnel delete — Delete a tunnel.
- wrangler tunnel run — Run a tunnel using the cloudflared daemon.
- wrangler tunnel quick-start — Start a free, temporary tunnel without an account using Quick Tunnels.
Wrangler handles downloading and managing the cloudflared binary automatically. On first use, you will be prompted to download cloudflared to a local cache directory.

These commands are currently experimental and may change without notice.

To get started, refer to the Wrangler tunnel commands documentation.

Mar 16, 2026

@cloudflare/codemode v0.2.1: MCP barrel export, zero-dependency main entry point, and custom sandbox modules

Agents Workers

The latest releases of @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
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 });

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
TypeScript

// Before
import { generateTypes } from "@cloudflare/codemode";

// After
import { generateTypes } from "@cloudflare/codemode/ai";

// 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
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"

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

npm i @cloudflare/codemode@latest

See the Code Mode documentation for the full API reference.

Mar 14, 2026

Access Durable Object name via `ctx.id.name`
Durable Objects Workers
When your Worker accesses a Durable Object via idFromName() or getByName(), the same name is now available on ctx.id.name inside the object — no need to pass it through method arguments or persist it in storage. This brings the runtime behavior in line with the Workers runtime types.

This is especially useful for alarms, where there is no calling client to pass the name as an argument. When an alarm handler runs, ctx.id.name will hold the same name the object was originally accessed with.
JavaScript
```
import { DurableObject } from "cloudflare:workers";

export class ChatRoom extends DurableObject {
  async getRoomName() {
    // ctx.id.name returns the name passed to getByName() or idFromName()
    return this.ctx.id.name;
  }
}

// Worker
export default {
  async fetch(request, env) {
    const stub = env.CHAT_ROOM.getByName("general");
    const roomName = await stub.getRoomName();
    return new Response(`Welcome to ${roomName}!`);
  },
};
```
ctx.id.name is undefined in the following cases:
- For Durable Objects created with newUniqueId().
- When accessed via idFromString(), even if the ID was originally created from a name.
- For names longer than 1,024 bytes.
This works the same way in local development with wrangler dev as it does in production. Run npm update wrangler to ensure you are on a version with this support.

For more information, refer to the Durable Object ID documentation.

Mar 06, 2026

Workflow steps now expose retry attempt number via step context
Workflows Workers
Cloudflare Workflows allows you to configure specific retry logic for each step in your workflow execution. Now, you can access which retry attempt is currently executing for calls to step.do():
TypeScript
```
await step.do("my-step", async (ctx) => {
  // ctx.attempt is 1 on first try, 2 on first retry, etc.
  console.log(`Attempt ${ctx.attempt}`);
});
```
You can use the step context for improved logging & observability, progressive backoff, or conditional logic in your workflow definition.

Note that the current attempt number is 1-indexed. For more information on retry behavior, refer to Sleeping and Retrying.

Mar 03, 2026

Workflows step limit increased to 25,000 steps per instance
Workflows Workers
Each Workflow on Workers Paid now supports 10,000 steps by default, configurable up to 25,000 steps in your wrangler.jsonc file:
```
{
  "workflows": [
    {
      "name": "my-workflow",
      "binding": "MY_WORKFLOW",
      "class_name": "MyWorkflow",
      "limits": {
        "steps": 25000
      }
    }
  ]
}
```
Previously, each instance was limited to 1,024 steps. Now, Workflows can support more complex, long-running executions without the additional complexity of recursive or child workflow calls.

Note that the maximum persisted state limit per Workflow instance remains 100 MB for Workers Free and 1 GB for Workers Paid. Refer to Workflows limits for more information.

Mar 01, 2026

Agents SDK v0.7.0: Observability rewrite, keepAlive, and waitForMcpConnections

Agents Workers

The latest release of the Agents SDK ↗ 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 — 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
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();

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 — no subscription code needed in the agent itself:

JavaScript
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);
      }
    }
  },
};

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.

`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
TypeScript

const dispose = await this.keepAlive();
try {
  const result = await longRunningComputation();
  await sendResults(result);
} finally {
  dispose();
}

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
TypeScript

const result = await this.keepAliveWhile(async () => {
  const data = await longRunningComputation();
  return data;
});

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.

For the full API reference and when-to-use guidance, refer to 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
TypeScript

export class ChatAgent extends AIChatAgent {
  // Default — waits up to 10 seconds
  // waitForMcpConnections = { timeout: 10_000 };

  // Wait forever
  waitForMcpConnections = true;

  // Disable waiting
  waitForMcpConnections = false;
}

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:

npm i agents@latest @cloudflare/ai-chat@latest

Feb 24, 2026

Agents SDK v0.6.0: RPC transport for MCP, optional OAuth, hardened schema conversion, and @cloudflare/ai-chat fixes
Agents Workers
The latest release of the Agents SDK ↗ 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
- TypeScript
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.
RPC transport is experimental. The API may change based on feedback. Refer to the tracking issue ↗ 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
- TypeScript
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 24, 2026

Better Windows support for Python Workers
Workers
Pywrangler ↗, the CLI tool for managing Python Workers and packages, now supports Windows, allowing you to develop and deploy Python Workers from Windows environments. Previously, Pywrangler was only available on macOS and Linux.

You can install and use Pywrangler on Windows the same way you would on other platforms. Specify your Worker's Python dependencies in your pyproject.toml file, then use the following commands to develop and deploy:
Terminal window
```
uvx --from workers-py pywrangler dev
uvx --from workers-py pywrangler deploy
```
All existing Pywrangler functionality, including package management, local development, and deployment, works on Windows without any additional configuration.

Requirements

This feature requires the following minimum versions:
- wrangler >= 4.64.0
- workers-py >= 1.72.0
- uv >= 0.29.8
To upgrade workers-py (which includes Pywrangler) in your project, run:
Terminal window
```
uv tool upgrade workers-py
```
To upgrade wrangler, run:
Terminal window
```
npm install -g wrangler@latest
```
To upgrade uv, run:
Terminal window
```
uv self update
```
To get started with Python Workers on Windows, refer to the Python packages documentation for full details on Pywrangler.

Feb 24, 2026

Write structured queries to filter and search your Workers logs and traces
Workers
Workers Observability now includes a query language that lets you write structured queries directly in the search bar to filter your logs and traces. The search bar doubles as a free text search box — type any term to search across all metadata and attributes, or write field-level queries for precise filtering.

Queries written in the search bar sync with the Query Builder sidebar, so you can write a query by hand and then refine it visually, or build filters in the Query Builder and see the corresponding query syntax. The search bar provides autocomplete suggestions for metadata fields and operators as you type.

The query language supports:
- Free text search — search everywhere with a keyword like error, or match an exact phrase with "exact phrase"
- Field queries — filter by specific fields using comparison operators (for example, status = 500 or $workers.wallTimeMs > 100)
- Operators — =, !=, >, >=, <, <=, and : (contains)
- Functions — contains(field, value), startsWith(field, prefix), regex(field, pattern), and exists(field)
- Boolean logic — add conditions with AND, OR, and NOT
Select the help icon next to the search bar to view the full syntax reference, including all supported operators, functions, and keyboard shortcuts.

Go to the Workers Observability dashboard ↗ to try the query language.

Feb 24, 2026

No config? No problem. Just `wrangler deploy`
Workers
You can now deploy any existing project to Cloudflare Workers — even without a Wrangler configuration file — and wrangler deploy will just work.

Starting with Wrangler 4.68.0, running wrangler deploy automatically configures your project by detecting your framework, installing required adapters, and deploying it to Cloudflare Workers.

Using Wrangler locally
Terminal window
```
npx wrangler deploy
```
When you run wrangler deploy in a project without a configuration file, Wrangler:
1. Detects your framework from package.json
2. Prompts you to confirm the detected settings
3. Installs any required adapters
4. Generates a wrangler.jsonc configuration file
5. Deploys your project to Cloudflare Workers
You can also use wrangler setup to configure without deploying, or pass --yes to skip prompts.

Using the Cloudflare dashboard

When you connect a repository through the Workers dashboard ↗, a pull request is generated for you with all necessary files, and a preview deployment to check before merging.

A pull request is only generated when your deploy command is npx wrangler deploy. If you use a custom deploy command, automatic configuration still runs but a PR is not created.

Background

In December 2025, we introduced automatic configuration as an experimental feature. It is now generally available and the default behavior.

If you have questions or run into issues, join the GitHub discussion ↗.

Feb 23, 2026

deleteAll() now deletes Durable Object alarm
Durable Objects Workers
deleteAll() now deletes a Durable Object alarm in addition to stored data for Workers with a compatibility date of 2026-02-24 or later. This change simplifies clearing a Durable Object's storage with a single API call.

Previously, deleteAll() only deleted user-stored data for an object. Alarm usage stores metadata in an object's storage, which required a separate deleteAlarm() call to fully clean up all storage for an object. The deleteAll() change applies to both KV-backed and SQLite-backed Durable Objects.
JavaScript
```
// Before: two API calls required to clear all storage
await this.ctx.storage.deleteAlarm();
await this.ctx.storage.deleteAll();

// Now: a single call clears both data and the alarm
await this.ctx.storage.deleteAll();
```
For more information, refer to the Storage API documentation.

Feb 23, 2026

Dropped event metrics, typed Pipelines bindings, and improved setup
Pipelines Workers
Cloudflare Pipelines ingests streaming data via Workers or HTTP endpoints, transforms it with SQL, and writes it to R2 as Apache Iceberg tables. Today we're shipping three improvements to help you understand why streaming events get dropped, catch data quality issues early, and set up Pipelines faster.

Dropped event metrics

When stream events don't match the expected schema, Pipelines accepts them during ingestion but drops them when attempting to deliver them to the sink. To help you identify the root cause of these issues, we are introducing a new dashboard and metrics that surface dropped events with detailed error messages.

Dropped events can also be queried programmatically via the new pipelinesUserErrorsAdaptiveGroups GraphQL dataset. The dataset breaks down failures by specific error type (missing_field, type_mismatch, parse_failure, or null_value) so you can trace issues back to the source.
```
query GetPipelineUserErrors(
  $accountTag: String!
  $pipelineId: String!
  $datetimeStart: Time!
  $datetimeEnd: Time!
) {
  viewer {
    accounts(filter: { accountTag: $accountTag }) {
      pipelinesUserErrorsAdaptiveGroups(
        limit: 100
        filter: {
          pipelineId: $pipelineId
          datetime_geq: $datetimeStart
          datetime_leq: $datetimeEnd
        }
        orderBy: [count_DESC]
      ) {
        count
        dimensions {
          errorFamily
          errorType
        }
      }
    }
  }
}
```
For the full list of dimensions, error types, and additional query examples, refer to User error metrics.

Typed Pipelines bindings

Sending data to a Pipeline from a Worker previously used a generic Pipeline<PipelineRecord> type, which meant schema mismatches (wrong field names, incorrect types) were only caught at runtime as dropped events.

Running wrangler types now generates schema-specific TypeScript types for your Pipeline bindings. TypeScript catches missing required fields and incorrect field types at compile time, before your code is deployed.
TypeScript
```
declare namespace Cloudflare {
  type EcommerceStreamRecord = {
    user_id: string;
    event_type: string;
    product_id?: string;
    amount?: number;
  };
  interface Env {
    STREAM: import("cloudflare:pipelines").Pipeline<Cloudflare.EcommerceStreamRecord>;
  }
}
```
For more information, refer to Typed Pipeline bindings.

Improved Pipelines setup

Setting up a new Pipeline previously required multiple manual steps: creating an R2 bucket, enabling R2 Data Catalog, generating an API token, and configuring format, compression, and rolling policies individually.

The wrangler pipelines setup command now offers a Simple setup mode that applies recommended defaults and automatically creates the R2 bucket and enables R2 Data Catalog if they do not already exist. Validation errors during setup prompt you to retry inline rather than restarting the entire process.

For a full walkthrough, refer to the Getting started guide.

Feb 19, 2026

@cloudflare/codemode v0.1.0: a new runtime agnostic modular architecture
Agents Workers
The @cloudflare/codemode ↗ package has been rewritten into a modular, runtime-agnostic SDK.

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.

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. 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
- TypeScript
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
- wrangler.toml
JSONC
{ "worker_loaders": [{ "binding": "LOADER" }], }
TOML
[[worker_loaders]] binding = "LOADER"
See the Code Mode documentation for full API reference and examples.

Upgrade
Terminal window
```
npm i @cloudflare/codemode@latest
```

Feb 16, 2026

Agents SDK v0.5.0: Protocol message control, retry utilities, data parts, and @cloudflare/ai-chat v0.1.0
Agents Workers
The latest release of the Agents SDK ↗ 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
- TypeScript
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
- TypeScript
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
- TypeScript
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 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.
- 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 15, 2026

Quick Editor devtools replaced with log viewer
Workers
Cloudflare has deprecated the Workers Quick Editor dev tools inspector and replaced it with a lightweight log viewer.

This aligns our logging with wrangler tail and gives us the opportunity to focus our efforts on bringing benefits from the work we have invested in observability, which would not be possible otherwise.

We have made improvements to this logging viewer based on your feedback such that you can log object and array types, and easily clear the list of logs. This does not include class instances. Limitations are documented in the Workers Playground docs.

If you do need to develop your Worker with a remote inspector, you can still do this using Wrangler locally. Cloning a project from your quick editor to your computer for local development can be done with the wrangler init --from-dash command. For more information, refer to Wrangler commands.

Feb 14, 2026

New Best Practices guide for Workers
Workers
A new Workers Best Practices guide provides opinionated recommendations for building fast, reliable, observable, and secure Workers. The guide draws on production patterns, Cloudflare internal usage, and best practices observed from developers building on Workers.

Key guidance includes:
- Keep your compatibility date current and enable nodejs_compat — Ensure you have access to the latest runtime features and Node.js built-in modules.
- wrangler.jsonc
- wrangler.toml
JSONC
{ "name": "my-worker", "main": "src/index.ts", // Set this to today's date "compatibility_date": "2026-06-04", "compatibility_flags": ["nodejs_compat"], }
TOML
name = "my-worker" main = "src/index.ts" # Set this to today's date compatibility_date = "2026-06-04" compatibility_flags = [ "nodejs_compat" ]
- Generate binding types with wrangler types — Never hand-write your Env interface. Let Wrangler generate it from your actual configuration to catch mismatches at compile time.
- Stream request and response bodies — Avoid buffering large payloads in memory. Use TransformStream and pipeTo to stay within the 128 MB memory limit and improve time-to-first-byte.
- Use bindings, not REST APIs — Bindings to KV, R2, D1, Queues, and other Cloudflare services are direct, in-process references with no network hop and no authentication overhead.
- Use Queues and Workflows for background work — Move long-running or retriable tasks out of the critical request path. Use Queues for simple fan-out and buffering, and Workflows for multi-step durable processes.
- Enable Workers Logs and Traces — Configure observability before deploying to production so you have data when you need to debug.
- Avoid global mutable state — Workers reuse isolates across requests. Storing request-scoped data in module-level variables causes cross-request data leaks.
- Always await or waitUntil your Promises — Floating promises cause silent bugs and dropped work.
- Use Web Crypto for secure token generation — Never use Math.random() for security-sensitive operations.
To learn more, refer to Workers Best Practices.

Feb 12, 2026

Introducing GLM-4.7-Flash on Workers AI, @cloudflare/tanstack-ai, and workers-ai-provider v3.1.1
Workers Agents 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 ↗ package and workers-ai-provider v3.1.1 ↗.

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 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 (env.AI.run()), the REST API at /run or /v1/chat/completions, AI Gateway, or via workers-ai-provider for the Vercel AI SDK.

Pricing is available on the model page or pricing page.

@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 ↗. 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 ↗ 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

Feb 10, 2026

Workers are no longer limited to 1000 subrequests
Workers
Workers no longer have a limit of 1000 subrequests per invocation, allowing you to make more fetch() calls or requests to Cloudflare services on every incoming request. This is especially important for long-running Workers requests, such as open websockets on Durable Objects or long-running Workflows, as these could often exceed this limit and error.

By default, Workers on paid plans are now limited to 10,000 subrequests per invocation, but this limit can be increased up to 10 million by setting the new subrequests limit in your Wrangler configuration file.
- wrangler.jsonc
- wrangler.toml
JSONC
{ "limits": { "subrequests": 50000, }, }
TOML
[limits] subrequests = 50_000
Workers on the free plan remain limited to 50 external subrequests and 1000 subrequests to Cloudflare services per invocation.

To protect against runaway code or unexpected costs, you can also set a lower limit for both subrequests and CPU usage.
- wrangler.jsonc
- wrangler.toml
JSONC
{ "limits": { "subrequests": 10, "cpu_ms": 1000, }, }
TOML
[limits] subrequests = 10 cpu_ms = 1_000
For more information, refer to the Wrangler configuration documentation for limits and subrequest limits.

Feb 10, 2026

Improved React Server Components support in the Cloudflare Vite plugin
Workers
The Cloudflare Vite plugin now integrates seamlessly @vitejs/plugin-rsc ↗, the official Vite plugin for React Server Components ↗.

A childEnvironments option has been added to the plugin config to enable using multiple environments within a single Worker. The parent environment can then import modules from a child environment in order to access a separate module graph. For a typical RSC use case, the plugin might be configured as in the following example:
vite.config.ts
```
export default defineConfig({
  plugins: [
    cloudflare({
      viteEnvironment: {
        name: "rsc",
        childEnvironments: ["ssr"],
      },
    }),
  ],
});
```
@vitejs/plugin-rsc provides the lower level functionality that frameworks, such as React Router ↗, build upon. The GitHub repository includes a basic Cloudflare example ↗.

Feb 08, 2026

Agents SDK v0.4.0: Readonly connections, MCP security improvements, x402 v2 migration, and custom MCP OAuth providers
Agents Workers
The latest release of the Agents SDK ↗ 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
- TypeScript
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
- TypeScript
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 05, 2026

Visualize data, share links, and create exports with the new Workers Observability dashboard
Workers
The Workers Observability dashboard ↗ has some major updates to make it easier to debug your application's issues and share findings with your team.

You can now:
- Create visualizations — Build charts from your Worker data directly in a Worker's Observability tab
- Export data as JSON or CSV — Download logs and traces for offline analysis or to share with teammates
- Share events and traces — Generate direct URLs to specific events, invocations, and traces that open standalone pages with full context
- Customize table columns — Improved field picker to add, remove, and reorder columns in the events table
- Expandable event details — Expand events inline to view full details without leaving the table
- Keyboard shortcuts — Navigate the dashboard with hotkey support
These updates are now live in the Cloudflare dashboard, both in a Worker's Observability tab and in the account-level Observability dashboard for a unified experience. To get started, go to Workers & Pages > select your Worker > Observability.

Feb 03, 2026

Visualize your Workflows in the Cloudflare dashboard
Workflows Workers
Cloudflare Workflows now automatically generates visual diagrams from your code

Your Workflow is parsed to provide a visual map of the Workflow structure, allowing you to:
- Understand how steps connect and execute
- Visualize loops and nested logic
- Follow branching paths for conditional logic
You can collapse loops and nested logic to see the high-level flow, or expand them to see every step.

Workflow diagrams are available in beta for all JavaScript and TypeScript Workflows. Find your Workflows in the Cloudflare dashboard ↗ to see their diagrams.

Jan 21, 2026

New Placement Hints for Workers
Workers
You can now configure Workers to run close to infrastructure in legacy cloud regions to minimize latency to existing services and databases. This is most useful when your Worker makes multiple round trips.

To set a placement hint, set the placement.region property in your Wrangler configuration file:
- wrangler.jsonc
- wrangler.toml
JSONC
{ "placement": { "region": "aws:us-east-1", }, }
TOML
[placement] region = "aws:us-east-1"
Placement hints support Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure region identifiers. Workers run in the Cloudflare data center ↗ with the lowest latency to the specified cloud region.

If your existing infrastructure is not in these cloud providers, expose it to placement probes with placement.host for layer 4 checks or placement.hostname for layer 7 checks. These probes are designed to locate single-homed infrastructure and are not suitable for anycasted or multicasted resources.
- wrangler.jsonc
- wrangler.toml
JSONC
{ "placement": { "host": "my_database_host.com:5432", }, }
TOML
[placement] host = "my_database_host.com:5432"
- wrangler.jsonc
- wrangler.toml
JSONC
{ "placement": { "hostname": "my_api_server.com", }, }
TOML
[placement] hostname = "my_api_server.com"
This is an extension of Smart Placement, which automatically places your Workers closer to back-end APIs based on measured latency. When you do not know the location of your back-end APIs or have multiple back-end APIs, set mode: "smart":
- wrangler.jsonc
- wrangler.toml
JSONC
{ "placement": { "mode": "smart", }, }
TOML
[placement] mode = "smart"

Jan 19, 2026

Use auxiliary Workers alongside full-stack frameworks
Workers
Auxiliary Workers are now fully supported when using full-stack frameworks, such as React Router and TanStack Start, that integrate with the Cloudflare Vite plugin. They are included alongside the framework's build output in the build output directory. Note that this feature requires Vite 7 or above.

Auxiliary Workers are additional Workers that can be called via service bindings from your main (entry) Worker. They are defined in the plugin config, as in the example below:
vite.config.ts
```
import { defineConfig } from "vite";
import { tanstackStart } from "@tanstack/react-start/plugin/vite";
import { cloudflare } from "@cloudflare/vite-plugin";

export default defineConfig({
  plugins: [
    tanstackStart(),
    cloudflare({
      viteEnvironment: { name: "ssr" },
      auxiliaryWorkers: [{ configPath: "./wrangler.aux.jsonc" }],
    }),
  ],
});
```
See the Vite plugin API docs for more info.

Jan 19, 2026

Import SQL files as additional modules by default
Workers
The .sql file extension is now automatically configured to be importable in your Worker code when using Wrangler or the Cloudflare Vite plugin. This is particular useful for importing migrations in Durable Objects and means you no longer need to configure custom rules when using Drizzle ↗.

SQL files are imported as JavaScript strings:
TypeScript
```
// `example` will be a JavaScript string
import example from "./example.sql";
```

Changelog

New @cloudflare/codemode/mcp export

Zero-dependency main entry point

Custom sandbox modules

Internal normalization and sanitization

Upgrade

Observability rewrite

keepAlive() and keepAliveWhile()

waitForMcpConnections

Other improvements

Upgrade

RPC transport for MCP

Optional OAuth for MCP connections

Hardened JSON Schema to TypeScript converter

@cloudflare/ai-chat fixes

Upgrade

Requirements

Using Wrangler locally

Using the Cloudflare dashboard

Background

Dropped event metrics

Typed Pipelines bindings

Improved Pipelines setup

Breaking changes

New features

DynamicWorkerExecutor

Usage

Wrangler configuration

Upgrade

Retry utilities

Per-connection protocol message control

@cloudflare/ai-chat v0.1.0

Synchronous queue and schedule getters

Other improvements

Upgrade

GLM-4.7-Flash — Multilingual Text Generation Model

@cloudflare/tanstack-ai v0.1.1 — TanStack AI adapters for Workers AI and AI Gateway

workers-ai-provider v3.1.1 — transcription, speech, reranking, and reliability

Resources

Readonly connections

Custom MCP OAuth providers

MCP SDK upgrade to 1.26.0

MCP OAuth callback URL security fix

Deprecate onStateUpdate in favor of onStateChanged

x402 v2 migration

Other improvements

Upgrade

New `@cloudflare/codemode/mcp` export

`keepAlive()` and `keepAliveWhile()`

`waitForMcpConnections`

`@cloudflare/ai-chat` fixes

`DynamicWorkerExecutor`

`@cloudflare/ai-chat` v0.1.0

Deprecate `onStateUpdate` in favor of `onStateChanged`