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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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    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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    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.
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    MIT
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    Provides 28 MCP tools to query KBO baseball data, including player stats, pitch arsenal, zone charts, usage patterns, and trend reports using a SQLite database.
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    MIT
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    Enables querying K League official data (rankings, matches, players) via SQL using natural language, with a pre-built SQLite database.
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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.
    Last updated
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    Exposes the Camptocamp.org API to LLMs, enabling querying of alpine routes, summit altitudes, and course descriptions with reliable data to avoid hallucinations.
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    Enables users to interact with the Griptonite indoor climbing app, allowing them to log climbs, browse routes and grades, and retrieve activity feeds and rankings.
    Last updated
    22
    MIT