gtfs-pro-mcp

gtfs-pro-mcp

MCP server that provides tools for querying live transit data (stops, departures, routes, vehicles, alerts) from any WP GTFS Pro site, enabling AI assistants to answer rider questions.

Category
Visit Server

README

gtfs-one-mcp

A Model Context Protocol server that turns any GTFS One transit site into a set of tools for AI assistants. Point it at an agency's WordPress site and Claude, ChatGPT, or any other MCP-compatible client can answer rider questions from the agency's live GTFS and GTFS-Realtime data — nearest stops, next departures, routes, live bus positions, and service alerts.

It talks to the site's public REST API (/wp-json/gtfs-one/v1/*) — no plugins, no database access, no credentials required. One MCP server covers one transit site (which may host multiple agency feeds).

Why this exists: the only other transit MCP servers are single-agency, hard-coded hobby projects. This one works with any GTFS One install, driven entirely by configuration.

Tools

Tool What it does
list_feeds List the transit feeds (agencies) configured on the site
find_nearby_stops Nearest stops to a lat/lon, with serving routes and next departures
search_stops Find stops by name, landmark, or stop code
get_stop_departures Next departures from a specific stop, across all routes
get_route_map A route's shape (path geometry) and the stops it serves
get_system_map Every route in the system with its stops
get_service_alerts Active GTFS-Realtime service alerts (empty = no active alerts)
get_live_vehicles Real-time vehicle positions (empty = none reporting right now)
geocode_address Address / place name → coordinates, biased to the service area

The realtime tools (get_service_alerts, get_live_vehicles) never error on missing data — an empty result means "nothing active right now," not "no service." The tool descriptions tell the AI this explicitly.

Requirements

  • Node.js 18 or newer
  • A transit website running GTFS One 1.5+ with its REST API publicly reachable

Configuration

Provide settings via a JSON config file or environment variables (env vars win where both are set). Only the site URL is required.

// gtfs-one.config.json
{
  "gtfs_one_url": "https://your-agency-site.org",
  "feed_id": "default",
  "cache_ttl_seconds": 30,
  "agency_name": "Your Transit Agency",
  "agency_description": "Public transit serving ... (cities, landmarks, region)."
}
Setting Env var Default Notes
gtfs_one_url GTFS_ONE_URL — (required) Base URL of the GTFS One site
feed_id GTFS_ONE_FEED_ID default Default feed so the AI needn't pass one each call
cache_ttl_seconds GTFS_ONE_CACHE_TTL 30 Local response cache; protects the WP site
agency_name GTFS_ONE_AGENCY_NAME Shown in server metadata
agency_description GTFS_ONE_AGENCY_DESCRIPTION Service-area context for the AI

Pass a non-default config path with --config /path/to/config.json or the GTFS_ONE_CONFIG env var.

Use with Claude Desktop

Edit claude_desktop_config.json (Settings → Developer → Edit Config) and add:

{
  "mcpServers": {
    "gtfs-one-transit": {
      "command": "npx",
      "args": ["-y", "gtfs-one-mcp"],
      "env": {
        "GTFS_ONE_URL": "https://your-agency-site.org",
        "GTFS_ONE_FEED_ID": "default",
        "GTFS_ONE_AGENCY_NAME": "Your Transit Agency"
      }
    }
  }
}

Restart Claude Desktop, then ask: "What bus stops are near <a place in the service area>?" or "When's the next bus from <stop name>?"

Windows users: Claude Desktop on Windows can't launch npx directly (it's a .cmd shim, not an executable), so the server silently fails to start and Claude falls back to web search. Wrap the command in cmd instead:

{
  "mcpServers": {
    "gtfs-one-transit": {
      "command": "cmd",
      "args": ["/c", "npx", "-y", "gtfs-one-mcp"],
      "env": {
        "GTFS_ONE_URL": "https://your-agency-site.org",
        "GTFS_ONE_FEED_ID": "default",
        "GTFS_ONE_AGENCY_NAME": "Your Transit Agency"
      }
    }
  }
}

After editing, fully quit Claude Desktop (right-click the system-tray icon → Quit — closing the window isn't enough) and reopen it.

Use with ChatGPT / other MCP clients

Any client that launches a local stdio MCP server works the same way — run npx -y gtfs-one-mcp with the same environment variables, or install globally:

npm install -g gtfs-one-mcp
GTFS_ONE_URL=https://your-agency-site.org gtfs-one-mcp

Remote / hosted connector (Streamable HTTP)

The stdio setup above only works in clients that launch a local process (classic Claude Desktop, Cursor, etc.). The Claude apps that use remote connectors — the newer desktop app and claude.ai on the web — instead add an MCP server by URL. For those, run the server in HTTP mode and host it somewhere with a public HTTPS address; then add that URL as a custom connector.

Run it in HTTP mode:

GTFS_ONE_URL=https://your-agency-site.org \
GTFS_ONE_AGENCY_NAME="Your Transit Agency" \
PORT=3000 \
gtfs-one-mcp-http        # or: npm run start:http

This serves the MCP endpoint at /mcp (and a /healthz check). Extra env:

Env Default Notes
PORT 3000 Most hosts inject this automatically
MCP_AUTH_TOKEN Optional. If set, clients must send Authorization: Bearer <token>. Leave unset for an open server — the transit data is public.

Deploy

  • Docker: a Dockerfile is included — docker build -t gtfs-one-mcp . && docker run -p 3000:3000 -e GTFS_ONE_URL=… -e GTFS_ONE_AGENCY_NAME=… gtfs-one-mcp
  • Render / Railway / Fly.io (Node): build npm install && npm run build, start npm run start:http, set the env vars. A render.yaml blueprint is included; Render gives you HTTPS automatically.
  • Your own VPS: run behind nginx/Caddy with TLS, proxying to the Node port.

The data is public and read-only, so an open endpoint is fine; add MCP_AUTH_TOKEN if you'd rather gate it.

Add it to Claude

In the Claude desktop app or claude.ai: Settings → Connectors → Add custom connector, give it a name, and paste your server's URL ending in /mcp (e.g. https://gtfs-one-mcp.onrender.com/mcp). Then ask a transit question and you'll see the gtfs-one-transit tools used.

Local development

npm install
npm run build       # compile TypeScript to dist/
node test/smoke.mjs # exercise all 9 tools against a live site

How it fits together

Local (stdio):
AI client  ──MCP/stdio──►  gtfs-one-mcp  ──HTTPS──►  GTFS One REST API
(Desktop)                  (local process)           /wp-json/gtfs-one/v1/*

Remote (Streamable HTTP):
AI client  ──MCP/HTTPS──►  gtfs-one-mcp-http  ──HTTPS──►  GTFS One REST API
(web/app)                  (hosted service /mcp)          /wp-json/gtfs-one/v1/*

Both transports share the same nine tools and config — pick stdio for local clients (Claude Desktop, Cursor) or HTTP for connector-based clients (the Claude app, claude.ai web, ChatGPT).

License

GPL-2.0-or-later © Digital Mountaineers

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