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    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.
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    MIT
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    Live sports betting player props MCP server covering NBA, MLB, NFL, NHL, NCAA, and soccer. Unified from real sportsbooks into one REST API and a real MCP server (Streamable HTTP). Free tier, no card required.
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    MIT
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    Provides a tool to retrieve today's 2026 FIFA World Cup matches, including teams, time, venue, and scores.
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    Provides access to Fantasy NBA Israel League statistics including team rankings, player stats, roster details, and shooting analytics for a specific private fantasy basketball league.
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    Real-time tennis data for ATP, WTA, Challenger and ITF: live scores, player rankings, match-winner odds, and model win-probability. 12 read-only tools; a tier-gated endpoint returns a plain-English explanation of which plan it needs rather than a bare 403. Requires a paid API key.
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    A physics-aware inline skating combo generator that models moves as state transitions to ensure sequences are executable and flow naturally. It allows users to generate custom skating routines and browse a catalog of wizard-style tricks.
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    MIT
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    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.
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    Provides Formula One data and statistics through a Model Context Protocol interface, allowing users to access race calendars, session results, driver statistics, telemetry data, and championship standings.
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    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.
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    Connect AI agents to OP.GG Esports data and retrieve upcoming League of Legends match schedules effortlessly. Access structured match information through a standardized interface, enhancing your AI's capabilities with real-time esports data.
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    Provides natural language access to IPL cricket match data, allowing users to query player statistics, team performances, and match results. It utilizes a SQLite backend and Cricsheet data to deliver detailed cricket analytics through the Model Context Protocol.
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    A Model Context Protocol server for the Sportmonks Football API v3, providing over 150 tools to access football data including fixtures, teams, players, odds, predictions, and more.
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    AI soigneur for cyclists: turns your Strava ride into an Ien-Vitse-validated nutrition plan (carbs/hour, hydration, timing) and assembles a ready-to-order musette. Works alongside the Strava MCP in Claude and ChatGPT.
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    MIT
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    Wraps TheSportsDB API to enable AI agents to query sports data through natural language.
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    MIT
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    A Model Context Protocol server that provides read-only access to Yahoo Fantasy Sports data, enabling AI assistants to query league standings, player stats, matchups, and rosters.
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    Provides read-only access to Sleeper fantasy football leagues, enabling team snapshots, available players, matchups, trade context, and league history through standardized MCP tools.
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    MIT
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    Enables interaction with a Token Bowl fantasy football league through the Sleeper API, providing tools for league operations, player data, and chat features.
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    Turns official pickleball scoring rules into callable tools for LLMs to track live matches accurately.
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    MIT
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    Props-first sports odds API with a hosted MCP server. Live odds and player props (moneyline, spreads, totals) across US sportsbooks, normalized to JSON. Tools: get_odds, get_props, get_events, get_books. API-key auth, free tier.
    Last updated
    MIT No Attribution