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"Adding functionality to large language models" matching MCP servers:

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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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    2
    MIT
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    Provides comprehensive access to Strava API for marathon training and race analysis, enabling language models to query athlete data, analyze training patterns, track performance metrics, monitor heart rate zones, and detect injury risks.
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    MIT
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    Interprets advanced hockey player cards to translate metrics into plain-language assessments, supporting player evaluation, claim verification, and player comparisons with deterministic rules.
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    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.
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    MIT
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    Enables Claude to access live Premier League data—teams, matches, standings, rosters, player details, and schedule-strength analytics—through natural language.
    12
    MIT
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    Provides access to real-time data from the French Basketball Federation (FFBB), including live scores, standings, and competition details. It allows users to search for clubs, matches, and venues using natural language without requiring an API key.
    12
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    Apache 2.0
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    Provides access to Formula 1 data including driver and constructor championship standings with support for current and historical seasons. Enables users to query F1 championship information through natural language with plans for expanded race data and telemetry.
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    MIT
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    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.
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    MIT
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    Enables users to query MLB Statcast, FanGraphs, and Baseball Reference data using natural language through an AI assistant. It provides comprehensive tools for analyzing player performance, pitch-level data, season leaderboards, and team standings.
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    MIT
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    Provides access to KenPom basketball analytics through MCP tools. Enables querying ratings, efficiency, player stats, and more using natural language.
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    MIT
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    Connects Claude to your Strava fitness data, enabling natural language queries about your training history such as activities, stats, and routes.
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    An MCP server that connects Claude Desktop to Hudl, enabling live access to team stats, player stats, and game results through natural language queries.
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    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.
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    MIT
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    Exposes the StatsPlus API as tools for MCP-compatible clients, enabling users to query player/team statistics, contracts, ratings, and game history via natural language.
    15
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    MIT
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    Provides soccer match predictions and league statistics using xG data and Poisson distribution models. It enables users to forecast outcomes, analyze team performance, and view league tables across major European football leagues.
    3
    GPL 2.0
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    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.
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    MIT