eze-godoy/mcp-server-ns-bridge
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A Model Context Protocol (MCP) server that enables LLMs to interact with the Netherlands Railways (NS) API for route planning, pricing, and real-time departure information.
MCP Server for Netherlands NS Trains
mcp-name: ns-bridge
A Model Context Protocol (MCP) server that enables AI assistants to interact with the Netherlands Railways (NS) API for route planning, pricing, and real-time departure information.
Compatible with any MCP client, including Claude Desktop, custom implementations, and AI agent frameworks.
Features
MCP Tools
-
search_stations - Find train stations by name or country
- Search by station name
- Filter by country code
- Returns station codes needed for trip planning
-
search_trips - Plan routes between stations
- Get multiple trip options with connections
- View detailed leg-by-leg journey information
- See pricing with discount options
- Choose travel class (1st or 2nd)
- Search by departure or arrival time
-
get_departures - View real-time departure boards
- See upcoming departures from any station
- Track delays and cancellations
- Monitor platform changes
MCP Resources
station://{code}- Get detailed information about a specific station
Installation
Prerequisites
- NS API key from NS API Portal
- Choose one installation method:
- Docker (easiest - no Python installation needed)
- uv (recommended for development)
- pip (traditional Python workflow)
Option 1: Docker (Easiest)
Prerequisites: Docker Desktop or Docker Engine
# Pull the pre-built image from Docker Hub
docker pull ezegodoy26/mcp-server-ns-bridge:latest
Then configure your MCP client (see Usage section below for configuration examples).
For detailed Docker usage, troubleshooting, and advanced options, see .
Option 2: Setup with uv (Recommended for Development)
# Clone the repository
cd mcp-server-ns-bridge
# Install dependencies
uv sync --all-extras
# Set up pre-commit hooks (recommended for development)
uv run pre-commit install
# Copy environment template
cp .env.example .env
# Edit .env and add your NS API key
# NS_API_KEY=your_actual_api_key_here
Option 3: Setup with pip
# Create virtual environment
python -m venv .venv
source .venv/bin/activate # On Windows: .venv\Scripts\activate
# Install dependencies
pip install -e ".[dev]"
# Set up environment
cp .env.example .env
# Edit .env and add your NS API key
Getting an NS API Key
- Go to NS API Portal
- Create an account
- Subscribe to the following APIs:
- Reisinformatie API (Travel Information)
- NS-APP Stations API
- Copy your subscription key
- Add it to your
.envfile asNS_API_KEY
Usage
Running the MCP Server
Development Mode (with Inspector)
export PATH="$HOME/.local/bin:$PATH"
uv run mcp dev src/ns_bridge/server.py
This opens the MCP Inspector for interactive testing.
Configuring MCP Clients
This server works with any MCP-compatible client. Below are configuration examples for popular clients.
Claude Desktop
Automatic Installation:
uv run mcp install src/ns_bridge/server.py
This will automatically configure Claude Desktop to use your MCP server.
Manual Configuration:
Add to your Claude Desktop config file (location varies by OS):
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json
Linux: ~/.config/Claude/claude_desktop_config.json
For Docker installation:
{
"mcpServers": {
"ns-bridge": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"--init",
"-e",
"NS_API_KEY",
"ezegodoy26/mcp-server-ns-bridge:latest"
],
"env": {
"NS_API_KEY": "your_api_key_here"
}
}
}
}
Note: The
-e NS_API_KEYin theargsarray tells Docker to pass the environment variable from the host (set by theenvsection) into the container. Without this, the API key won't be available inside Docker.
For uv installation:
{
"mcpServers": {
"ns-bridge": {
"command": "uv",
"args": [
"--directory",
"/absolute/path/to/mcp-server-ns-bridge",
"run",
"src/ns_bridge/server.py"
],
"env": {
"NS_API_KEY": "your_api_key_here"
}
}
}
}
After updating the configuration, restart your MCP client to load the server.
Other MCP Clients
For other MCP-compatible clients (custom implementations, AI agent frameworks, etc.), refer to your client's documentation for stdio server configuration. The server accepts standard MCP protocol messages via stdin/stdout.
Example Queries
Once configured, you can ask your AI assistant:
- "What trains are departing from Utrecht Centraal in the next hour?"
- "Find me a train from Amsterdam to Rotterdam tomorrow at 9 AM"
- "What's the fastest route from Den Haag to Groningen?"
- "How much does a first-class ticket from Eindhoven to Maastricht cost?"
- "Show me stations near the German border"
Development
Project Structure
mcp-server-ns-bridge/
├── src/
│ └── ns_bridge/
│ ├── __init__.py # Package initialization
│ ├── server.py # MCP server implementation
│ ├── ns_api_client.py # NS API wrapper
│ ├── models.py # Data models (Pydantic)
│ └── config.py # Configuration management
├── tests/ # Test suite
├── pyproject.toml # Project configuration & dependencies
├── .env.example # Environment template
└── README.md # This file
Developer Tools
This project uses modern Python development tools for code quality:
Pre-commit Hooks
Pre-commit hooks automatically check your code before each commit:
- General checks: Trailing whitespace, EOF fixes, YAML/TOML validation
- Ruff: Fast linting and code formatting
- MyPy: Static type checking
- Bandit: Security vulnerability scanning
# Install pre-commit hooks (one-time setup)
uv run pre-commit install
# Run manually on all files
uv run pre-commit run --all-files
# Hooks will automatically run on git commit
Code Formatting & Linting
You can also run tools manually:
# Format code with Ruff
uv run ruff format src/ tests/
# Lint and auto-fix
uv run ruff check --fix src/ tests/
# Type checking
uv run mypy src/
# Security scanning
uv run bandit -r src/
See for detailed documentation on each tool and why we use them.
Testing
- pytest: Test framework
- pytest-asyncio: Async test support
- pytest-cov: Code coverage
- pytest-httpx: HTTP mocking for API tests
Run tests:
# Run all tests
uv run pytest
# Run with coverage
uv run pytest --cov
# Run specific test file
uv run pytest tests/test_models.py
# Run with verbose output
uv run pytest -v
Virtual Environment Note
Yes, uv is compatible with virtual environments! uv automatically creates and manages a .venv directory in your project. You can activate it manually if needed:
source .venv/bin/activate # macOS/Linux
.venv\Scripts\activate # Windows
However, uv run automatically uses the virtual environment, so activation is optional for most tasks.
API Documentation
NS API Endpoints Used
-
Stations API (
/nsapp-stations/v2)- Search and list train stations
- Filter by country
-
Trips API (
/reisinformatie-api/api/v3/trips)- Route planning with connections
- Pricing information
- Support for via stations
-
Departures API (
/reisinformatie-api/api/v2/departures)- Real-time departure information
- Delay and cancellation tracking
Station Codes
Common station codes:
ut- Utrecht Centraalasd- Amsterdam Centraalrtd- Rotterdam Centraalgvc- Den Haag Centraalehv- Eindhoven Centraalnm- Nijmegengn- Groningen
Use the search_stations tool to find more station codes.
Contributing
Suggestions and improvements are welcome!
Development Workflow
- Create a feature branch
- Make your changes
- Run the test suite:
uv run pytest - Pre-commit hooks will automatically run on commit (or run manually:
uv run pre-commit run) - Submit a pull request
Note: Pre-commit hooks automatically handle formatting, linting, type checking, and security scanning.
License
MIT License - see LICENSE file for details
Acknowledgments
- Model Context Protocol - Anthropic's MCP specification
- NS API - Netherlands Railways API
- FastMCP - Python MCP SDK
Roadmap
Future enhancements planned:
- Add support for disruptions API
- Include station facilities information
- Add journey details (crowdedness predictions)
- Support for international routes
- Caching for frequently accessed data
- Rate limiting to respect API quotas