cadence
Related Servers
Alternatives to cadence
No user-submitted related servers found.
Related Servers
- AlicenseNot gradedqualityDmaintenanceConnects your Whoop health data to Claude, enabling natural language queries about recovery, sleep, strain, and workouts.458 npmMIT
- -licenseNot gradedqualityNot gradedmaintenanceConnects WHOOP fitness data to Claude Desktop, enabling natural language queries about workouts, recovery, sleep patterns, and health metrics while keeping data secure and private.-
- AlicenseAqualityDmaintenanceGives Claude access to your WHOOP health data including recovery, sleep, workouts, cycles, body measurements, and profile via the WHOOP Developer API.714 npmMIT
- AlicenseNot gradedqualityDmaintenanceExposes Whoop fitness data (recovery, sleep, strain, workouts) to Claude for use as a daily training coach, enabling natural language queries about your health metrics and training readiness.MIT
- FlicenseAqualityBmaintenanceProvides Claude Desktop with access to WHOOP fitness data including recovery, sleep, strain, and workouts.41-
- AlicenseNot gradedqualityFmaintenanceConnects WHOOP fitness data to Claude Desktop, enabling natural language queries about workouts, recovery, sleep patterns, and physiological cycles with secure OAuth authentication and local data storage.458 npm27MIT
TDQS
Scored across 6 tools
Each tool targets a distinct aspect of health data: daily metric time series, WHOOP recovery, sleep sessions, trend comparison, workouts, and a natural-language summary. Descriptions clearly differentiate overlapping metrics by source and form (e.g., resting heart rate in get_daily_metric vs. in get_recovery).
All six tools follow a consistent get_<noun> pattern in snake_case. No mixing of styles or verbs, making the tool surface predictable.
Six tools is well-scoped for a health data aggregation server: one for daily metrics, recovery, sleep, trends, workouts, and a summary. Each tool serves a clear purpose without redundancy.
The tool set covers the main areas of personal health data (daily metrics, recovery, sleep, workouts, trends, summary). A minor gap is the lack of intraday or raw sensor data, but given the focus on daily aggregates and summaries, the coverage is strong.