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Model Context Protocol (MCP) Server

@AdamPippert

代码仓库

关于 Model Context Protocol (MCP) Server

an MCP server for the services I like to use with AI agents, which you should probably fork and modify for your own use. No PRs accepted, this is just for me. Not private because you or a bot might get something out of what you see here.

基本信息

分类

其他

许可证

Apache-2.0

运行时

python

传输方式

stdio

发布者

AdamPippert

配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "multi-service-mcp-server": {
      "command": "python",
      "args": [
        "app.py"
      ]
    }
  }
}

工具

未检测到工具

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is Model Context Protocol (MCP) Server?

Model Context Protocol (MCP) Server is a modular, container‑ready server that implements the Model Context Protocol standard. It provides a unified gateway and direct access to tools for GitHub, GitLab, Google Maps, Memory (persistent key‑value store), and Puppeteer web automation. Note: This project is no longer being maintained.

How to use Model Context Protocol (MCP) Server?

Install Python 3.8+ and Node.js 14+, clone the repository, install dependencies (pip install -r requirements.txt, npm install), configure a .env file with secrets and API keys, then run python app.py. The server listens on port 5000 by default. Access the MCP Gateway at POST /mcp/gateway or reach individual tools via /tool/<toolname>/....

Key features of Model Context Protocol (MCP) Server

  • Unified MCP Gateway endpoint for all tool requests
  • MCP Manifest endpoint describing available tools and capabilities
  • Direct per‑tool API endpoints (GitHub, GitLab, Google Maps, Memory, Puppeteer)
  • Modular architecture for adding or removing tools
  • Containerized deployment with Docker or Podman (including SELinux support)
  • Persistent memory storage via SQLite (configurable)

Use cases of Model Context Protocol (MCP) Server

  • Aggregate GitHub and GitLab repository, issue, and pipeline operations in one server
  • Perform geocoding, directions, and places lookups from Google Maps
  • Store and retrieve temporary data across AI sessions using the Memory tool
  • Automate web tasks like screenshots, PDFs, and content extraction via Puppeteer
  • Provide a single MCP‑compliant entry point for multiple backend services

FAQ from Model Context Protocol (MCP) Server

What does the server do?

It implements the Model Context Protocol to offer a unified gateway for tools that interact with GitHub, GitLab, Google Maps, a persistent memory store, and Puppeteer web automation.

What are the prerequisites?

Python 3.8+, Node.js 14+, and a Red Hat–based Linux distribution, other Linux, or macOS. Docker or Podman are needed for containerized deployment.

How do I configure API keys?

Create a .env file with variables such as GITHUB_TOKEN, GITLAB_TOKEN, GMAPS_API_KEY, and others as documented in the README.

Is this project still maintained?

No. The README clearly states the project is no longer being maintained because the author prefers individual containerized servers over a monolithic routing server.

What transport and authentication does the server use?

The server uses HTTP (Flask web framework) and runs on port 5000. Authentication is handled via secret keys and API tokens configured in the .env file.

评论

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