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Deutsche Bahn MCP Server

@PaulvonBerg

代码仓库

关于 Deutsche Bahn MCP Server

A comprehensive Model Context Protocol (MCP) server that provides unified access to Deutsche Bahn (DB) and German mobility APIs. Built with Python, FastAPI, and FastMCP for seamless integration with Claude Desktop and other MCP clients.

#deutsche-bahn#transport#mobility#infrastructure#mobilit-t

基本信息

分类

数据库

传输方式

stdio

发布者

PaulvonBerg

提交者

Paul von Berg

配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "deutschebahn": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-remote",
        "https://db-mcp.datamonkey.tech/mcp",
        "--transport",
        "http-only"
      ]
    }
  }
}

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 Deutsche Bahn MCP Server?

The Deutsche Bahn MCP Server provides access to comprehensive Deutsche Bahn railway data—stations, timetables, real-time disruptions, and parking—through the Model Context Protocol (MCP). It is designed for developers and AI agents that need structured, up‑to‑date railway information.

How to use Deutsche Bahn MCP Server?

Deploy the server (recommended on Google Cloud Run) and connect your MCP client. Full setup and configuration instructions are available in the rich documentation provided with the server.

Key features of Deutsche Bahn MCP Server

  • Complete railway data: stations, timetables, disruptions, parking
  • Full MCP protocol support (tools, prompts, resources)
  • Production ready: security headers, rate limiting, input validation
  • Modular, maintainable codebase architecture
  • Cloud‑native design for Google Cloud Run deployment

Use cases of Deutsche Bahn MCP Server

  • Query real‑time train schedules and platform changes
  • Retrieve current disruption and parking information for a station
  • Automate travel planning and route checks in AI assistants
  • Integrate Deutsche Bahn data into custom applications via MCP

FAQ from Deutsche Bahn MCP Server

What railway data does the server provide?

It offers stations, timetables, real‑time disruptions, and parking information.

Does it support the MCP protocol?

Yes, it provides full support for tools, prompts, and resources via the Model Context Protocol.

Where can I deploy this server?

It is designed for Google Cloud Run, with a cloud‑native architecture that simplifies deployment.

Is it production ready?

Yes, it includes security headers, rate limiting, and input validation for safe use in production.

How is the codebase structured?

It follows a modular architecture with a clean, maintainable codebase.

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