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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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    538
    MIT
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    Ask your Oura Ring about sleep, readiness, activity, stress and heart rate in ChatGPT or Claude, in any language. Read-only, 10 task-oriented tools; runs in a sandbox demo mode with no credentials.
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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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    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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    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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    Enables Claude to read your WHOOP health data including recovery, sleep, strain, and workouts through the official WHOOP API, so you can ask natural language questions about your fitness metrics.
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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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    Apple HealthKit → PostgreSQL sync + MCP server for Claude Code, Cursor, and Ollama. Open-source iOS app with reliable background sync (HKObserverQuery). 11 tools covering health summary, sleep, HRV trends, workouts, daily snapshots, metric stats, period comparison, and coaching briefs. Supports Supabase, Neon, and self-hosted Postgres. Privacy-first: your data goes to your own database.
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    MIT
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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