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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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    MCP server that provides F1 telemetry analysis, tyre degradation modeling, and pit strategy recommendations, delivering race engineer-style calls grounded in real data. It exposes tools for degradation fits, fuel correction, and strategy reasoning via LangGraph.
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    MIT
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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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    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.
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    MIT
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    Enables fast real-time web search and access to premium data from trusted sources including news, financial markets, sports, and more. Supports AI agents with live data and curated content from various domains.
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    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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    Enables triathlon coaches and athletes to interact with Garmin Connect, including retrieving health/activity data, building and uploading structured workouts (cycling, running, swimming, brick), and accessing coaching analytics like readiness, load, and performance trends.
    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.
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    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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    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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    Searchable football data provider documentation for AI coding agents. Enables agents to look up verified docs on event types, qualifier IDs, coordinate systems, and more across 15 providers.
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    MIT