"Information about Python programming or Python-related topics" matching MCP servers:

This project implements a Model Context Protocol (MCP) server providing Formula One racing data using the Python FastF1 library. Inspired by an existing TypeScript server, it offers similar F1 data functionalities natively in Python via FastF1.

Provides access to live NHL game data, team and player statistics, standings, schedules, playoff information, and head-to-head comparisons through natural language queries using official NHL APIs.

Enables AI assistants to access World Cube Association speedcubing data including world records, competitor profiles, competition information, and championship results. Supports queries about rankings, competition schedules, and detailed speedcubing statistics through natural language.

Connects Claude to your Strava fitness data, enabling natural language queries about your training history such as activities, stats, and routes.

Enables AI agents to search and retrieve detailed information about US golf courses, including course details, tees, climate, and nearby points of interest.

MCP server for Formula 1 data via the FastF1 library. Ask Claude (or any MCP-compatible client) about race results, lap times, telemetry, standings, pit stops, and qualifying — with historical data back to 1950 via the Ergast API.

Provides professional cycling data from FirstCycling, allowing users to retrieve comprehensive information about cyclists, race results, historical cycling data, and team information through natural language queries.

An MCP Server implementation that integrates the Balldontlie API, to provide information about players, teams and games for the NBA, NFL and MLB.

Python MCP server that provides comprehensive access to MLB statistics and baseball data through a FastAPI-based interface. Acts as a bridge between AI applications and MLB data sources, enabling seamless integration of baseball statistics, game information, player data, and more.

Enables answering questions about your disc golf rounds, courses, hole-by-hole scores and scoring trends, plus practice-throw speed, distance, spin and angle, read entirely from your own CSV exports with no credentials or network access.

Provides comprehensive Formula 1 data access including race schedules, session results, lap times, telemetry data, driver/constructor standings, and circuit information. Enables users to retrieve and analyze F1 racing data through natural language queries using the FastF1 Python package.

A Model Context Protocol server that provides access to Fantasy Premier League data, allowing users to compare players, find team information, view gameweek data, and get FPL-related advice through Claude for Desktop and other MCP-compatible clients.

A Python MCP server providing 11 tools for querying KenPom basketball analytics, including efficiency ratings, game predictions, four factors, and more through Claude.

A minimal Python MCP server that provides surf forecasts for a single Surfline spot. It fetches both conditions and rating data through the get_surf_forecast tool.

Enables fetching football fixtures, match details, league tables, and squad information from the matchday app through natural language.

A Python-based MCP server that extracts football match data from multiple global sources like ESPN and BBC Sport using intelligent web scraping. It enables AI assistants to retrieve scheduled matches, real-time scores, and broadcasting details with advanced filtering for high-profile games.

Connects Claude to a personal Garmin Connect account so users can ask natural-language questions about sleep, HRV, body battery, stress, heart rate, training readiness and activities, and optionally create or schedule workouts and log weigh-ins. Reads are returned as trimmed summaries with optional full JSON, and writes stay disabled unless explicitly enabled.

Provides live Formula 1 data such as driver standings, race results, and schedule for the current season, enabling users to ask about F1 without stale training data.

Enables read-only access to WHOOP recovery, sleep, HRV, strain, and workout data so users can ask natural-language questions about their personal health history, trends, and baselines inside Claude, Codex, or GitHub Copilot. It also provides HYROX and triathlon session analysis, race readiness checks, and a local performance dashboard.

Answers lineup, trade, waiver, and playoff-odds questions by running deterministic Python analysis and returning conclusions, not raw data.