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kirollosatef

google-health-mcp

by kirollosatef

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Alternatives to google-health-mcp

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    Related Servers

    • A
      license
      Not graded
      quality
      C
      maintenance
      Enables Claude and other MCP clients to query your Fitbit/Pixel Watch health data via the Google Health API, including sleep, heart rate, activity, workouts, and trends with read-only access.
      11 npm
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    • F
      license
      Not graded
      quality
      B
      maintenance
      Enables AI agents to query locally stored Samsung Health data—such as heart rate, sleep, steps, and workouts—through MCP tools for samples, daily summaries, and trend analysis while keeping everything on your own network.
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    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables AI agents to query personal health data collected by any wearable or phone fitness app through Android Health Connect or Apple Health, exposing read-only tools for metrics like heart rate, sleep stages, VO2 max, and body composition. It can run locally over USB with nothing stored, or be self-hosted on Cloudflare Workers with D1 to retain history beyond Health Connect's 30-day limit.
      14 npm
      MIT
    • A
      license
      Not graded
      quality
      D
      maintenance
      Gives Claude read access to wearable health data from Fitbit or Wear OS devices via the Google Health API, exposing tools for metrics like steps, heart rate, sleep, and workouts, plus a computed recovery score.
      1
      MIT
    • A
      license
      A
      quality
      A
      maintenance
      Enables AI agents to securely access Apple Health data (sleep, heart rate, menstrual cycle, etc.) via end-to-end encrypted local decryption from the Tether iOS app.
      33
      125 PyPI
      2
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables Claude to read, write, and delete Google Health (Fitbit successor) metrics such as activity, sleep, heart rate, weight, and nutrition, plus log meals with photo-based nutrition estimation.
      MIT

    TDQS

    A4.1/5.0

    Scored across 9 tools

    Disambiguation5/5

    Each tool has a clearly distinct purpose: auth check, data type listing, profile, daily multi-metric brief, weekly trend, readiness, anomaly scan, raw points, and daily aggregate. No overlap between tools; health_daily_brief and health_daily differ by scope (single day vs range) and metric count.

    Naming Consistency5/5

    All tools follow a consistent health_ prefix with descriptive snake_case suffixes (auth_status, data_types, profile, daily_brief, trend, readiness, anomalies, points, daily). The pattern is uniform and predictable.

    Tool Count5/5

    9 tools is a well-scoped number for a health data server. Each tool covers a distinct aspect of reading and analyzing health metrics without redundancy or bloat.

    Completeness4/5

    The tool surface covers authentication, data discovery, profile, daily snapshots, trends, readiness, anomalies, raw data, and daily aggregates. Minor gap: no direct way to get multiple metrics across a date range in one call, but this can be composed from existing tools.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues