xtuc
MCP Serverxtucpublic

mcp workers ai

MCP servers sdk for Cloudflare Workers

Repository Info

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JavaScript
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-
License

About This Server

MCP servers sdk for Cloudflare Workers

Model Context Protocol (MCP) - This server can be integrated with AI applications to provide additional context and capabilities, enabling enhanced AI interactions and functionality.

Documentation

MCP Workers AI

MCP servers sdk for Cloudflare Workers

Usage

Install:

yarn add mcp-workers-ai
# or
npm install -S mcp-workers-ai

Load the MCP server tools:

import { loadTools } from "mcp-workers-ai"

const tools = await loadTools([
  import("@modelcontextprotocol/server-gitlab"),
  import("@modelcontextprotocol/server-slack"),
  ...
]);

// Pass `tools` to the LLM inference request.

Call a tool:

import { callTool } from "mcp-workers-ai"

// Typically the LLM selects a tool to use.
const selected_tool = {
  arguments: {
    project_id: 'svensauleau/test',
    branch: 'main',
    files: [ ... ],
    commit_message: 'added unit tests'
  },
  name: 'push_files'
};

const res = await callTool(selected_tool)

// Pass `res` back into a LLM inference request.

Demo

wrangler configuration:

name = "test"
main = "src/index.ts"

[ai]
binding = "AI"

[vars]
GITLAB_PERSONAL_ACCESS_TOKEN = "glpat-aaaaaaaaaaaaaaaaaaaa"

[alias]
"@modelcontextprotocol/sdk/server/index.js" = "mcp-workers-ai/sdk/server/index.js"
"@modelcontextprotocol/sdk/server/stdio.js" = "mcp-workers-ai/sdk/server/stdio.js"

Worker:

import { loadTools, callTool } from "mcp-workers-ai"

export default {
  async fetch(request: Request, env: any): Promise<Response> {
    // Make sure to set the token before importing the tools
    process.env.GITLAB_PERSONAL_ACCESS_TOKEN = env.GITLAB_PERSONAL_ACCESS_TOKEN;

    const tools = await loadTools([
      import("@modelcontextprotocol/server-gitlab/dist/"),
    ]);

    const prompt = await request.text();

    const response = await env.AI.run(
      "@hf/nousresearch/hermes-2-pro-mistral-7b",
      {
        messages: [{ role: "user", content: prompt }],
        tools,
      },
    );

    if (response.tool_calls && response.tool_calls.length > 0) {
      const selected_tool = response.tool_calls[0];
      const res = await callTool(selected_tool)

      if (res.content.length > 1) {
        throw new Error("too many responses")
      }

      const finalResponse = await env.AI.run(
        "@hf/nousresearch/hermes-2-pro-mistral-7b",
        {
          messages: [
            {
              role: "user",
              content: prompt,
            },
            {
              role: "assistant",
              content: "",
              tool_call: selected_tool.name,
            },
            {
              role: "tool",
              name: selected_tool.name,
              content: res.content[0].text,
            },
          ],
          tools,
        },
      );
      return new Response(finalResponse.response);

    } else {
      return new Response(response.response);
    }
  }
};

Calling the AI:

$ curl http://example.com \
  -d "create a file called 'joke.txt' in my svensauleau/test project with your favorite joke on the main branch. Use the commit message 'added unit tests'"

I have successfully added a file called 'joke.txt' with a joke to your project 'svensauleau/test' on the main branch. The commit message used was 'added unit tests'. You can view the commit and the file in your project's repository.

Result: !demo

Quick Start

1

Clone the repository

git clone https://github.com/xtuc/mcp-workers-ai
2

Install dependencies

cd mcp-workers-ai
npm install
3

Follow the documentation

Check the repository's README.md file for specific installation and usage instructions.

Repository Details

Ownerxtuc
Repomcp-workers-ai
LanguageJavaScript
License-
Last fetched8/10/2025

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