garmin-personal-mcp
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Alternatives to garmin-personal-mcp
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Related Servers
- FlicenseNot gradedqualityCmaintenanceEnables AI assistants to access and query Garmin Connect health and fitness data, including sleep, HRV, training load, and activities, with an optional coaching plugin for personalized training plans.3 npm4-
- AlicenseNot gradedqualityCmaintenanceEnables AI assistants to retrieve and discuss personal fitness activities, training splits, heart-rate zones, and daily health metrics from a Garmin Connect account.MIT
- AlicenseAqualityBmaintenanceEnables AI assistants to query a user's own Garmin Connect training, health, and recovery history through Garmin's official Personal API, backed by a local cache and built-in analysis tools.21394 npm2Apache 2.0
- AlicenseNot gradedqualityBmaintenanceEnables reading and analyzing Garmin Connect data—activities, health metrics, FIT files, and challenges—through natural language, for AI assistants like Claude and ChatGPT.MIT
- AlicenseAqualityBmaintenanceEnables an AI assistant to read Garmin Connect sleep, health, activity, and training data, and to write structured multi-sport workouts, calendar schedules, and performance metrics back into Garmin Connect.2418 npm1MIT
- AlicenseNot gradedqualityDmaintenanceEnables AI agents to access Garmin Connect activities, workouts, and workout templates for querying and creating workout plans.6MIT
TDQS
Scored across 20 tools
Most tools have clearly distinct targets, and the activity sub-tools (getActivity, getActivityLaps, getActivitySets, getActivityWorkouts) are explicitly differentiated with cross-references ("getActivity does not have them"). There is mild overlap between getDailySummary and the individual getters (getDailyHeartRate, getBodyBattery), and between getDashboardData and the per-domain readers, but descriptions largely resolve it. The garminGet escape hatch is clearly framed as a fallback.
Names are uniformly camelCase with a predictable verb_noun pattern: get*, list*, download*, write*, edit*, show*, schedule*. The main deviation is garminGet, which uses a noun-prefix style inconsistent with everything else, but overall the convention is readable and predictable.
Twenty tools is on the heavier side, but the Garmin domain is genuinely broad (activities, sleep, HRV, HR, weight, body battery, zones, fitness age) and each reader covers a distinct endpoint. The five dashboard tools form a coherent subsystem (read, write, edit, show, schedule) rather than redundant surface.
Read coverage is extensive across health, activity, and training domains, and the dashboard lifecycle plus a generic garminGet fallback make most workflows achievable. The main gap is the absence of writes back to Garmin (logging weight, uploading activities), though this appears to be a read-focused personal server by design.