MCP server
by cloudflare
Cloudflare Workers empowers MCP to deploy scalable, low-latency AI services at the network edge for optimal performance.
Connects Claude Desktop to Cloudflare Workers by translating TypeScript Worker methods into MCP tools via a local proxy server.
Cloudflare Workers is an official MCP server published by cloudflare that provides AI assistants with tools and capabilities via the Model Context Protocol. Cloudflare Workers empowers MCP to deploy scalable, low-latency AI services at the network edge for optimal performance. It is categorized under cloud infrastructure, developer tools.
You can install Cloudflare Workers in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
Apache-2.0
Cloudflare Workers is released under the Apache-2.0 license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Share your MCP server with the developer community
We wired Cloudflare Workers into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
Cloudflare Workers reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
Cloudflare Workers has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
I recommend Cloudflare Workers for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
We evaluated Cloudflare Workers against two servers with overlapping tools; this profile had the clearer scope statement.
Useful MCP listing: Cloudflare Workers is the kind of server we cite when onboarding engineers to host + tool permissions.
According to our notes, Cloudflare Workers benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
We evaluated Cloudflare Workers against two servers with overlapping tools; this profile had the clearer scope statement.
Cloudflare Workers is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
Cloudflare Workers has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
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workers-mcpTalk to a Cloudflare Worker from Claude Desktop!
[!WARNING]
You should start here instead — and build a remote MCP serverYou can connect to remote MCP servers from Claude Desktop, Cursor, and other clients using mcp-remote.
workers-mcp?This package provides both the CLI tooling and the in-Worker logic to connect Claude Desktop (or any MCP Client) to a Cloudflare Worker on your account, so you can customise it to suit your needs. It works via a build step that can translate TypeScript methods of your Worker like this:
export class ExampleWorkerMCP extends WorkerEntrypoint<Env> {
/**
* Generates a random number. This is extra random because it had to travel all the way to
* your nearest Cloudflare PoP to be calculated which... something something lava lamps?
*
* @return {string} A message containing a super duper random number
* */
async getRandomNumber() {
return `Your random number is ${Math.random()}`
}
// ...etc
}
...into MCP tools that a local Node.js server can expose to MCP clients. The Node.js server acts as a proxy, handling stdio transport locally, and calling the relevant method of your Worker running on Cloudflare. This allows you to expose any function or API in your app, or any service in Cloudflare's developer platform, back to a LLM in your coding agent, Claude Desktop or other MCP client.
<sub>Yes, I know that
Math.random()works the same on a Worker as it does on your local machine, but don't tell Claude</sub> 🤫
Use create-cloudflare to generate a new Worker.
npx create-cloudflare@latest my-new-worker
I suggest choosing a Hello World worker.
workers-mcpcd my-new-worker # I always forget this bit
npm install workers-mcp
setup commandnpx workers-mcp setup
Note: if something goes wrong, run npx workers-mcp help
After changing your Worker code, you only need to run npm run deploy to update both Claude's metadata about your function and your live Worker instance.
However, if you change the names of your methods, or their parameters, or add or remove methods, Claude will not see the updates until you restart it.
You shouldn't ever need to rerun npx workers-mcp install:claude, but it's safe to do so if you want to rule out Claude config as a source of errors.
To get your Cloudflare MCP server working in Cursor, you need to combine the 'command' and 'args' from your config file into a single string and use type 'command'.
For example, if your config file looks like:
{
"mcpServers": {
"your-mcp-server-name": {
"command": "/path/to/workers-mcp",
"args": [
"run",
"your-mcp-server-name",
"https://your-server-url.workers.dev",
"/path/to/your/project"
],
"env": {}
}
}
}
In Cursor, create an MCP server entry with:
command/path/to/workers-mcp run your-mcp-server-name https://your-server-url.workers.dev /path/to/your/projectFor Windsurf and other MCP clients, update your configuration file to include your worker so you could use the tools directly from the client:
{
"mcpServers": {
"your-mcp-server-name": {
"command": "/path/to/workers-mcp",
"args": [
"run",
"your-mcp-server-name",
"https://your-server-url.workers.dev",
"/path/to/your/project"
],
"env": {}
}
}
}
Make sure to replace the placeholders with your actual server name, URL, and project path.
See the examples directory for a few ideas of what to use this for:
examples/01-hello-world is a snapshot taken after the installation instructions aboveexamples/02-image-generation uses Workers AI to run the Flux image generation model. Claude is really good at suggesting prompts and can actually interpret the outcome and decide what new prompts to try to achieve the outcome you want.Prerequisites
Time Estimate
15-60 minutes depending on server complexity
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
Compatibility
✓ Use when
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid when
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.