SBB Open Data MCP Server

SBB Open Data MCP Server

An MCP server for Swiss Federal Railways (SBB) open data, enabling AI models to query real-time disruptions, passenger frequencies, station details, and more without an API key.

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SBB Open Data MCP Server

🇩🇪 Deutsch | 🇬🇧 English

An Model Context Protocol (MCP) server for Swiss Federal Railways (SBB) open data via data.sbb.ch. No API key required.

Python License: MIT MCP


What is this?

This server connects AI models (Claude, GPT-4, Llama, etc.) directly to public SBB data — no copy-pasting or manual API calls required. A question like "How many passengers passed through Zürich HB every day in 2024?" is answered with real measured data.

The server is model-agnostic and works with any MCP-compatible client.


Available Tools (10)

Tool Description Data Update
sbb_get_passenger_frequency Boardings/alightings by station and year (daily avg.) Annual
sbb_get_rail_disruptions Live rail traffic messages Every 5 min.
sbb_get_infrastructure_construction_projects Infrastructure construction (stations, lines) Ongoing
sbb_get_real_estate_projects SBB real estate development projects Daily
sbb_get_trains_per_segment Train counts per route segment (SBB, BLS, SOB …) Annual
sbb_get_platform_data Platform data (length, type, area) Ongoing
sbb_get_rolling_stock Rolling stock (capacity, year built) Ongoing
sbb_compare_stations Compare up to 10 stations (multi-dataset)
sbb_search_stations Search stops (Swiss DiDok register, all CH) Ongoing
sbb_list_datasets List all ~89 SBB open datasets

All tools support response_format: "markdown" (human-readable) and "json" (machine-readable), plus pagination.


Installation

Prerequisites

Install uv:

curl -LsSf https://astral.sh/uv/install.sh | sh

Claude Desktop (stdio)

Open the config file:

  • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
  • Windows: %APPDATA%\Claude\claude_desktop_config.json
{
  "mcpServers": {
    "sbb-opendata": {
      "command": "uvx",
      "args": ["sbb-opendata-mcp"]
    }
  }
}

Restart Claude Desktop. The server is downloaded automatically on first use.

Other MCP Clients

Works with Cursor, Windsurf, VS Code + Continue, LibreChat, Cline and self-hosted models via mcp-proxy — same configuration as above.

Cloud Deployment (Streamable HTTP)

For remote servers (e.g. Render.com):

git clone https://github.com/malkreide/sbb-opendata-mcp
cd sbb-opendata-mcp
pip install -e .
python -m sbb_opendata_mcp.server --http --port 8000

Local Development

git clone https://github.com/malkreide/sbb-opendata-mcp
cd sbb-opendata-mcp
pip install -e ".[dev]"

# Unit tests (no network required)
PYTHONPATH=src pytest tests/ -v -m "not live"

# Live API smoke tests
PYTHONPATH=src pytest tests/ -v -m live

Example Queries

"How many people boarded at Zürich HB daily in 2024?"
→ sbb_get_passenger_frequency(station_name="Zürich HB", year="2024")

"Are there any current disruptions on the Swiss rail network?"
→ sbb_get_rail_disruptions(limit=10)

"Compare Zürich HB, Bern and Basel SBB by passenger frequency and platform capacity."
→ sbb_compare_stations(stations=["Zürich HB", "Bern", "Basel SBB"], year="2024")

"Which SBB construction projects are active in Zürich?"
→ sbb_get_infrastructure_construction_projects(city="Zürich")

"How many trains run daily on the Zürich–Winterthur route?"
→ sbb_get_trains_per_segment(line_name="Zürich", operator="SBB", year="2025")

"Which stops exist in Wädenswil?"
→ sbb_search_stations(query="Wädenswil", canton="ZH")

Data & License

All data is sourced from the SBB Open Data Portal (OpenDataSoft REST API v2.1).
Data license: NonCommercialAllowed-CommercialAllowed-ReferenceRequired

This server is released under the MIT License and is part of the open source MCP portfolio at github.com/malkreide.


Relationship to Other MCP Servers

Server How SBB Open Data Complements It
swiss-transport-mcp Historical depth: passenger context for real-time timetable queries
swiss-road-mobility-mcp Multimodal view: rail hub + micromobility/EV charging
zurich-opendata-mcp Cross-reference: Zurich stops combined with city population and school data

Technical Details

  • Framework: FastMCP + httpx + Pydantic v2
  • Transport: stdio (local) and Streamable HTTP (cloud)
  • Python: 3.11, 3.12, 3.13
  • Tests: 34 unit tests + 5 live API smoke tests
  • API: OpenDataSoft REST v2.1 — no authentication needed

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