"Information about Python programming language or Python snakes" 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.

Bridges Suunto watch data to AI assistants like Claude, enabling natural language queries about workouts, sleep, and recovery.

MCP server that connects AI assistants to the Statos football analytics platform, enabling natural language queries for match predictions, betting picks, league information, and admin market-suppression controls.

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.

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.

A Model Context Protocol server that gives AI assistants real-time access to the MCSR Ranked competitive Minecraft speedrunning API, enabling plain-language queries about players, matches, stats, and more.

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.

Enables natural language interaction with Sleeper Fantasy Football API data, allowing queries about leagues, players, matchups, draft results, and trade analysis.

Enables querying Chess.com public data including player profiles, stats, games, and club information through natural language.

A Model Context Protocol server that provides comprehensive Formula One racing data, enabling access to event schedules, driver information, telemetry data, race results, and performance analytics through natural language queries.

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.

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 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.

Provides access to official MLB statistics via a keyless API, enabling AI agents to query MLB data through natural language or direct tools.

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