No install? Use cloud.anythingmcp.com directly.
Sign in, install the Deutsche Bahn Fahrplan in one click, paste the credentials, mint an MCP API key — done. No Docker, no git clone, no local server to run.
TL;DR
Query the Deutsche Bahn (DB) timetable via the community-maintained v6.db.transport.rest proxy over the official HAFAS API. Search stations, look up departures/arrivals in real time, and plan journeys between any two DB stops.
💡 Keine Installation? Nutze cloud.anythingmcp.com direkt. Einloggen, Connectors → Deutsche Bahn Fahrplan klicken, Zugangsdaten einfügen, MCP-API-Key erzeugen — fertig. Kein Docker, kein
git clone, kein lokaler Server.
Deutsche Bahn Fahrplan + Gemini
Query the Deutsche Bahn (DB) timetable via the community-maintained v6.db.transport.rest proxy over the official HAFAS API. Search stations, look up departures/arrivals in real time, and plan journeys between any two DB stops.
Voraussetzungen
Die vollständige Setup-Anleitung ist in den Connector eingebaut (im Store sichtbar, wenn du den Connector auswählst). Benötigte Umgebungsvariablen für diesen Connector:
(none — public API)
Schritt 1 — Zugangsdaten holen
db.transport.rest — a free, no-auth wrapper around Deutsche Bahn's HAFAS endpoints maintained by the public-transport community.
No authentication required, but the service is hosted best-effort — for production use you may want to self-host (see https://github.com/derhuerst/db-rest).
Typical workflow:
- Resolve a station name to a stop
idwithdb_search_locations - Call
db_get_departuresordb_get_arrivalswith that id - For trip planning, use
db_get_journeyswithfromandtostop ids
Time format: All times are ISO 8601 with timezone (e.g. 2026-04-21T08:30+02:00). If omitted, when defaults to now.
…(continued in the in-app connector instructions)
Schritt 2 — Adapter installieren
git clone https://github.com/HelpCode-ai/anythingmcp.git
cd anythingmcp && docker compose up -d
Schritt 3 — Connector in Gemini hinzufügen
Gemini CLI liest MCP-Server aus ~/.gemini/settings.json (oder %APPDATA%\gemini\settings.json unter Windows). Hinzufügen:
{
"mcpServers": {
"anythingmcp": {
"httpUrl": "https://cloud.anythingmcp.com/mcp",
"headers": { "Authorization": "Bearer YOUR_MCP_API_KEY" }
}
}
}
- Hole deinen MCP API Key aus AnythingMCP → Profil → MCP API Keys → Neuer Key.
- Speichern und
geminineu starten. /mcpin Gemini CLI ausführen —Deutsche Bahn Fahrplansollte als verfügbar gelistet sein.- Vertex AI Studio:
https://cloud.anythingmcp.com/mcpimtools-Array der Anfrage mit demselben Bearer-Header übergeben.
Verfügbare Tools
| Tool | What it does |
|---|---|
db_search_locations | Search for DB stops/stations, addresses, or points of interest by name |
db_get_stop | Retrieve details for a specific stop/station by its DB id, including name, location, station category, and products served (ICE, IC, RE, S, |
db_get_departures | List upcoming departures from a stop |
db_get_arrivals | List upcoming arrivals at a stop with origin, planned and actual time, platform, delay, and cancellation status |
db_get_journeys | Plan a journey between two stops |
FAQ
Unterstützen Gemini 1.5 Pro oder 2.x MCP? Ja — Gemini CLI ≥ 0.4 und die Vertex AI Tools API akzeptieren MCP httpUrl-Connectors mit Bearer-Header.
Nächste Schritte
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