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MCP Server

@AdamPippert

代码仓库

基本信息

分类

其他

许可证

Apache-2.0

传输方式

stdio

作者

AdamPippert

关于 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.

MCP Server 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"
      ]
    }
  }
}

MCP Server 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

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

常见问题

1

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.

2

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.

3

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.

4

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.

5

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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