garmin-connect-mcp-server
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Alternatives to garmin-connect-mcp-server
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Related Servers
- AlicenseAqualityCmaintenanceMCP server that connects Garmin Connect to Claude Desktop, allowing users to query health and fitness data (sleep, workouts, heart rate, HRV, stress, Body Battery, etc.) in plain English and also log weight, hydration, and schedule workouts.25MIT
- FlicenseAqualityCmaintenanceA local MCP server that exposes Garmin Connect activity, health, and training data as tools for Claude Desktop. It provides read-only access to metrics like activities, sleep, heart rate, and training readiness.25-
- AlicenseNot gradedqualityBmaintenanceA local, read-only MCP server that gives Claude access to your Garmin health and training data, exposing tools for health snapshots, training status, run details, body metrics, and training analysis.MIT
- AlicenseNot gradedqualityDmaintenanceAn MCP server that gives Claude access to your Garmin Connect fitness and health data, including steps, sleep, activities, heart rate, and more.1MIT
- AlicenseAqualityBmaintenanceLocal MCP server that connects Claude Desktop with Garmin and Apple Health data to read training and recovery, estimate heart rate and pace zones, analyze performance, and create structured workouts.22MIT
- AlicenseNot gradedqualityBmaintenanceA local, single-user, read-only MCP server that gives Claude Code access to your Garmin health and training data, exposing tools for health snapshots, training status, run details, body metrics, and training analysis.1MIT
TDQS
Scored across 6 tools
Each tool targets a unique aspect of Garmin data: daily summary, activity detail, training status, body composition, sleep, and activity list. No two tools overlap in purpose, making selection unambiguous.
Tools follow a 'garmin_verb_noun' pattern (e.g., garmin_get_daily_summary, garmin_get_sleep), with 'garmin_list_activities' being the only one using 'list' instead of 'get'. This minor inconsistency is easily understood but breaks the pattern slightly.
With 6 tools covering key health and fitness domains (daily metrics, activities, training, body composition, sleep), the count feels well-scoped and sufficient for a read-only health data API.
The tool surface covers essential read-only operations: retrieving daily summaries, activity details, training status, body composition, sleep, and listing activities. Cross-references between tools indicate thoughtful design, with no obvious missing functionality for the intended purpose.