google-health-mcp
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Alternatives to google-health-mcp
No user-submitted related servers found.
Related Servers
- AlicenseAqualityDmaintenanceAn MCP server that locally authenticates with Google Health API v4 and provides read-only access to Fitbit, Pixel Watch, and other health data for AI agents.29164 npm16MIT
- AlicenseNot gradedqualityDmaintenanceSelf-hosted MCP server that aggregates personal health data from Google Health, Oura, and Withings into a single, provider-attributed interface with configurable source of truth preferences.MIT
- AlicenseNot gradedqualityCmaintenanceRead-only MCP server for Apple Health data, exposing tools to query current health stats, sleep/health details, and trends over 7, 14, or 30 days.MIT
- AlicenseNot gradedqualityBmaintenanceRead-only MCP access to Fitbit-synced health data through Google Health API v4. Provides tools for metrics, summaries, trends, and data quality without write or arbitrary HTTP operations.MIT
- AlicenseAqualityDmaintenanceMCP 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.5MIT
- AlicenseAqualityAmaintenanceMCP server for the Google Health API: heart rate, activity, sleep, SpO2, HRV, ECG and irregular-rhythm notifications, read into a local SQLite cache for fast offline queries and trend analysis. OAuth 2.0 with automatic token refresh, incremental sync, a cache-only offline mode, and a doctor command that diagnoses a setup without spending quota.241,939 PyPIGPL 3.0
TDQS
Scored across 7 tools
Tools have distinct purposes but some overlap exists: get_daily_health_facts and get_daily_health_pulse both return daily summaries (one factual, one narrative), and get_health_history vs get_health_records both provide data at different granularities. Descriptions help differentiate, but minor ambiguity remains.
All tool names follow the verb_noun pattern with snake_case, consistently using 'get_' prefix. The naming is uniform and predictable (e.g., get_daily_health_facts, get_health_data_catalog).
With 7 tools, the set is well-scoped for a health data server. Each tool serves a distinct purpose (daily summary, history, records, catalog, status, time window) without unnecessary bloat or deficiency.
The tool set provides thorough read-only coverage: daily facts, narrative summaries, historical trends, full-fidelity records, time-window queries, and metadata. Missing write operations (create/update/delete) are reasonable if the server is query-only. Minor gaps like direct metric extraction are mitigated by history and records tools.