get_event_scheduleLABSCO SUMMARY
Race data at the level people actually argue about.
Results tell you who won; lap times and telemetry tell you where it happened. Both sit behind the same connection, so a question about a season can narrow to a single lap without changing tools.
What it is
Access to Formula One timing data — the season calendar, event details, session results, driver records, lap times, telemetry and championship standings — served from the FastF1 library.
What you get
- The race calendar for a given season
- Details of a single Grand Prix, addressed by name or by round number
- Results for any session — race, qualifying, sprint, or a practice run
- Driver information for a session, addressed by number, code or name
- Lap times and telemetry behind a driver's performance in a session
- A comparison across several drivers
- Driver and constructor championship standings
Requirements
Node.js 18 or later and Python 3.8 or later, with fastf1, pandas and numpy installed, then a build of the TypeScript. No account and no key.
Setup effort
Build from source — git clone https://github.com/rakeshgangwar/f1-mcp-server.git
USE CASES
01
Settling an argument about a specific race
Pull the session results for that weekend rather than the summary someone half-remembers.
02
Seeing where a lap was won
Read the lap times and the telemetry behind them for that driver in that session.
03
Comparing two drivers over a weekend
Put their performances side by side inside the same session instead of reading two result tables.
04
Following a title fight through the season
Take the driver and constructor standings and read them against the calendar of what is left.
8 tools
Listed in project docs. Your client may show a different list.
get_event_infoget_session_resultsget_driver_infoanalyze_driver_performancecompare_driversget_telemetryget_championship_standingsBEFORE YOU INSTALL
What to know first
Tools you get
8 tools named in the project's documentation.
Requires
- Node.js 18 or later
- Python 3.8 or later
Where it runs
The documented client runs the server on your machine.
INSTALLATION
Connect your client
Server setup
TERMINAL
git clone https://github.com/rakeshgangwar/f1-mcp-server.git
pip install fastf1 pandas numpy
cd f1-mcp-server
npm install
npm run buildMCP Clients
Cline
CLINE · JSON
{
"mcpServers": {
"formula1": {
"command": "node",
"args": [
"<YOUR_PATH_TO_F1_MCP_SERVER>/build/index.js"
],
"disabled": false,
"autoApprove": []
}
}
}<YOUR_PATH_TO_F1_MCP_SERVER> is the full path of the f1-mcp-server folder you cloned — npm run build writes build/index.js there.
