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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.
    8
    2
    MIT
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    MCP server that connects Garmin Connect data to Claude, enabling training analysis, recovery checks, and personalized plans based on real metrics like HRV, training load, and activities.
    12
    MIT
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    Enables AI assistants to read Garmin activities and create/schedule structured workouts and multi-week training plans directly on Garmin Connect, syncing to your watch with guided prompts.
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    MIT
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    Connect ESPN & Yahoo fantasy leagues to AI assistants via MCP. Read-only tools for rosters, standings, matchups, free agents, and league info across football and baseball.
    10
    MIT
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    Exposes Garmin Connect data through MCP, enabling retrieval of activities, health metrics, training status, and workouts, with OAuth authentication and confirmed write operations.
    MIT
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    Provides read access to Garmin Connect health and training data (sleep, heart rate, stress, HRV, activities) and supports writes like creating workouts, editing activities, and exporting files.
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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.
    5
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    Read/write MCP server for Intervals.icu — 51 tools spanning activities, streams, wellness, calendar, gear, and sport zones, plus structured workout generation with a built-in syntax reference for cycling, running, and swimming.
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    MIT
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    A lightweight Garmin Model Context Protocol server with 12 curated endpoints for endurance athletes, enabling natural-language queries of activity, training, health, device, and goal data from Garmin Connect.
    12
    MIT
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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.
    24
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    MIT
  • F
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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 AI agents with access to football match predictions for Premier League and Champions League, including half-time/full-time scores, goal scorers, corner counts, and key player insights.
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    Enables AI agents to interact with ActiveNet OpenAPI services for managing organizations, activities, customers, facilities, and more.
    GPL 2.0
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    Wraps TheSportsDB API to enable AI agents to query sports data through natural language.
    MIT