What is MCP?
MCP stands for Model Context Protocol, a protocol for providing tools to AI models. MCP Workers AI enables using MCP servers with Cloudflare Workers.
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Basic information
MCP servers sdk for Cloudflare Workers
No standard config provided
This server doesn't expose a parseable MCP config block in its README. See the repository for install instructions.
RepositoryTool list not available yet
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We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
MCP Workers AI is an SDK for integrating Model Context Protocol (MCP) server tools with Cloudflare Workers. It allows developers to load multiple MCP servers (e.g., GitLab, Slack) and call their tools from Worker scripts, feeding the results into Cloudflare Workers AI model inference requests.
Install the package via npm or yarn, then import loadTools and callTool. Configure your Worker with an AI binding and necessary environment variables (e.g., tokens for external services). In a fetch handler, load the MCP tools, send a user prompt to a Workers AI model, and handle any tool calls the model returns.
MCP stands for Model Context Protocol, a protocol for providing tools to AI models. MCP Workers AI enables using MCP servers with Cloudflare Workers.
You need a Cloudflare Workers project with an AI binding (`[ai] binding = "AI"`) and environment variables for the external services you connect to (e.g., `GITLAB_PERSONAL_ACCESS_TOKEN`).
Tool data is fetched from the external services at the time of invocation. The Worker environment holds credentials; no data is stored permanently by the SDK.
Any standard MCP server module compatible with the `@modelcontextprotocol/sdk` can be imported. Examples include `@modelcontextprotocol/server-gitlab` and `@modelcontextprotocol/server-slack`.
The SDK exports `callTool`, which takes an object with `name` and `arguments` (typically provided by the AI model) and returns the tool’s response. That response can then be fed back into a subsequent AI inference call.

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