Deutsche Bahn MCP Server
About
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.
Details
- Author
- PaulvonBerg
- Downloads
- 384
- Categories
- Database, Infrastructure
Jump to
- 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
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
Deutsche Bahn MCP ServerCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
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.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"deutsche bahn mcp server": {
"deutschebahn": {
"command": "npx",
"args": [
"-y",
"mcp-remote",
"https://db-mcp.datamonkey.tech/mcp",
"--transport",
"http-only"
]
}
}
}
}McpServers
{
"deutschebahn": {
"command": "npx",
"args": [
"-y",
"mcp-remote",
"https://db-mcp.datamonkey.tech/mcp",
"--transport",
"http-only"
]
}
}🚀 Features
🚄 Complete Railway Data: Stations, timetables, real-time disruptions, and parking
🤖 MCP Protocol: Full support for tools, prompts, and resources
🛡️ Production Ready: Security headers, rate limiting, input validation
🏗️ Modular Architecture: Clean, maintainable codebase structure
☁️ Cloud Native: Designed for Google Cloud Run deployment
📚 Rich Documentation: Comprehensive guides and reference materials
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