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    Provides a unified MCP interface to a personal health database, enabling AI agents to sync lifting workouts from Hevy, log food intake against a catalog, and run read-only SQL queries to cross-reference training and nutrition data.
    6
    1
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    Provides comprehensive running performance calculations including VDOT, training paces, race time predictions, velocity markers, and heart rate zones using Jack Daniels, Greg McMillan, and Riegel methodologies.
    9
    MIT
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    Local MCP server that reorders YouTube Music playlists for running, using YouTube Data API to read, validate, and reorder tracks with dry-run and safe copy creation.
    7
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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.
    11
    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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    MIT
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    Enables searching FatSecret's food and recipe database, and managing personal food diary, weight, exercise, saved meals, and favorites, with multi-user support and secure OAuth authentication.
    28
    Apache 2.0
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    MCP server for accessing Oura Ring data from Claude Code and claude.ai, providing summarized health metrics and raw API data.
    11
    MIT
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    A personal fitness tracking server that enables logging and querying workouts, nutrition, and body metrics through a local SQLite database. Integrates with OpenNutrition MCP for food logging and supports exercise history tracking for workout progression.
    17
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    Provides local MCP tools to query your own Xiaomi Mi Fitness health data (sleep, workouts, heart rate, etc.) stored in a local SQLite database, enabling AI assistants to access personal health records without exposing credentials.
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    AGPL 3.0
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    Enables reading and syncing Xiaomi Mi Fitness health data (steps, heart rate, sleep, workouts) from the Chinese cloud region to a local SQLite database via MCP tools.
    10
    3
    MIT