Model Context Protocol server for Caltrain schedules
Wellknown found it in public sources; nobody has proven control of it yet. Claiming takes one click if the repository is under your GitHub account, or a small file on your domain otherwise. Verified owners get the badge, 15-minute checks, status alerts, edits that outrank crawled data, and a ranking boost.
Agents can do it too: POST https://wellknown.network/api/v1/claims with {"agent":"caltrain-mcp","method":"well_known_file"} — machine-readable steps at claim.json, guide at /docs/claim.
Everything here was measured by our prober or read from a registry. Nothing is self-reported.
Attributed to the source that supplied each field. Treated as claims, not facts.
# 🚂 Caltrain MCP Server (Because You Love Waiting for Trains) [](https://pypi.org/project/caltrain-mcp/) [](https://github.com/davidyen1124/caltrain-mcp/actions/workflows/ci.yml)  A Model Context Protocol (MCP) server that promises to tell you _exactly_ when the next Caltrain will arrive... and then be 10 minutes late anyway. Uses real GTFS data, so at least the disappointment is official! ## Features (Or: "Why We Built This Thing") - 🚆 **"Real-time" train schedules** - Get the next departures between any two stations (actual arrival times may vary by +/- infinity) - 📍 **Station lookup** - Because apparently 31 stations is too many to memorize 🤷♀️ - 🕐 **Time-specific queries** - Plan your commute with surgical precision, then watch it all fall apart - ✨ **Smart search** - Type 'sf' instead of the full name because we're all lazy here - 📊 **GTFS-based** - We use the same data Caltrain does, so when things go wrong, we can blame them together ## Setup (The Fun Part 🙄) 1. **Install dependencies** (aka "More stuff to break"): ```bash # Install uv if you haven't already (because pip is apparently too mainstream now) curl -LsSf https://astral.sh/uv/install.sh | sh # Install dependencies using uv (fingers crossed it actually works) uv sync ``` 2. **Get that sweet, sweet GTFS data**: The server expects Caltrain GTFS data in the `src/caltrain_mcp/data/caltrain-ca-us/` directory. Because apparently we can't just ask the trains nicely where they are. ```bash uv run python scripts/fetch_gtfs.py ``` This magical script downloads files that contain: - `stops.txt` - All the places trains pretend to stop - `trips.txt` - Theoretical journeys through space and time - `stop_times.txt` - When trains are _supp…
Mapped onto the structured taxonomy from declared text and observed tool names. Confidence shown for derived entries.
Every source is kept verbatim. Field changes are logged as events.