Garmin Health MCP Server
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Alternatives to Garmin Health MCP Server
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Related Servers
- AlicenseBqualityAmaintenanceEnables users to analyze their own Garmin Connect data—activities, sleep, HRV, Body Battery, training readiness—directly inside Claude Desktop.132MIT
- FlicenseNot gradedqualityDmaintenanceConnects Garmin watch data to Claude Desktop, allowing users to ask natural language questions about their health and activity data from Garmin Connect.-
- AlicenseBqualityAmaintenanceConnects Claude Desktop to Garmin Connect, enabling natural language queries of fitness activity data, health metrics, sleep analysis, workout management, and device information with 94 available tools.1101MIT
- AlicenseBqualityBmaintenanceEnables Claude to access and query your Garmin Connect data—sleep, training, heart rate, and more—through a suite of read-only tools, with an optional write path for creating strength workouts.63MIT
- AlicenseNot gradedqualityBmaintenanceEnables Claude and any MCP client to read a user's own Garmin account in plain language, covering activities, time-series charts, thresholds, sleep, HRV, Body Battery, stress, readiness and trends. It also serves a private local dashboard that downloads the full training and health history, correlates metrics across views, and exports any table as CSV.MIT
- AlicenseAqualityAmaintenanceEnables Claude to read your own Garmin Connect data—activities and exact pace splits, VO2 max and training effect, sleep, HRV, Body Battery, stress, weight and more—through Garmin's official Personal API, with no password or scraping. Access is read-only and runs entirely on your machine, so you can ask natural-language questions about training and recovery.23153 npmMIT
TDQS
Scored across 9 tools
Each tool has a clearly distinct purpose targeting specific health metrics or functions, with no overlap in scope. The tools cover different data types like activities, body battery, heart rate, HRV, sleep, stress, summaries, and profiles, making them easily distinguishable.
All tools follow a consistent verb_noun pattern with 'get_' or 'generate_' prefixes, using snake_case uniformly. This predictable naming scheme enhances readability and reduces confusion for agents.
With 9 tools, the server is well-scoped for a health data domain, covering key metrics without being overwhelming. Each tool serves a specific, necessary function, making the count appropriate for comprehensive health monitoring.
The toolset provides broad coverage for retrieving health metrics, including core data like activities, sleep, and stress, with a summary tool for aggregation. A minor gap exists in update or management tools for user data, but retrieval operations are largely complete for the domain.