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    MCP server to read daily activity, sleep, heart rate, and body metrics from Google Health API, allowing AI assistants like Claude to access your health data. Optionally syncs health metrics to an Obsidian vault.
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    5
    MIT
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    An MCP server that provides access to detailed exercise-to-muscle mapping data for over 320 exercises and 65 muscles. It enables users to analyze workout coverage, find exercise alternatives based on muscle overlap, and search for specific exercise activation data.
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    MIT
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    An AI-powered running coach that connects Claude to your Strava data, providing personalized training plans, progress tracking, and coaching feedback through a web dashboard.
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    MIT
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    Local-first MCP server that connects AI agents to your Garmin sleep, HRV, Body Battery, stress, training readiness and activities, keeping tokens on your machine.
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    An MCP server that interfaces with the Hevy fitness tracking API, enabling AI assistants to manage workouts, routines, exercise templates, and more via natural language.
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    26
    4,276
    MIT
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    Enables Claude Desktop to access and analyze Garmin wearable health data including sleep, HRV, Body Battery, and activity metrics. Users can query their health trends, track recovery, and generate interactive HTML dashboards using natural language.
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    5
    MIT
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    Trainzilla MCP connects Claude to your Trainzilla coach account, turning your client roster, programming, and habit tracking into something you can manage conversationally. Built for fitness coaches running their practice on Trainzilla, it lets Claude pull up client profiles and metrics, build and review workout and diet plans, create and assign habits, run quick calculations (TDEE, macros, 1RM),
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    An MCP server for Garmin Connect that provides access to fitness activities, health statistics, and sleep data by routing requests through a headless browser to bypass API restrictions. It enables users to query detailed metrics like heart rate zones, body battery, and GPS tracks using any MCP-compatible client.
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    AGPL 3.0
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    Enables users to interact with their Strava data through natural language to analyze workouts, track fitness progress, and explore routes. It supports retrieving detailed activity stats, heart rate data, and segment insights directly within AI assistants.
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    26
    538
    MIT