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garmin-mcp

garmin-mcp

by Lander-garmin
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

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    • garmin-mcp

      Tyler-Irving
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      Enables Claude to access and query your Garmin Connect data, including sleep, activities, training load, and health metrics, through a set of read-only MCP tools.
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    • Daash

      Bartolome69
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      Daash connects Garmin Connect to ChatGPT and Claude. Your assistant reads your runs, splits, sleep, HRV, Body Battery and recovery, and writes structured workouts and whole training plans to your Garmin calendar, so they're on your watch at the next sync. Free, hosted, open source. Works on free Claude.
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    • garmin-personal-api-mcp

      aaronhaddad
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      Enables 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.
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    • garmin-mcp

      alyssindewonderland
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      Connects Claude to a personal Garmin Connect account so users can ask natural-language questions about sleep, HRV, body battery, stress, heart rate, training readiness and activities, and optionally create or schedule workouts and log weigh-ins. Reads are returned as trimmed summaries with optional full JSON, and writes stay disabled unless explicitly enabled.
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    Deploy Server
    One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

    TDQS

    B3.2/5.0

    Scored across 63 tools

    Disambiguation2/5

    Many tools have fuzzy boundaries: get_daily_summary, get_daily_briefing, and get_stats_and_body all return overlapping daily snapshots, and get_recent_activities, get_activities_by_date, and get_last_activity serve nearly the same retrieval purpose. Activity-level tools like get_activity_details, get_activity_timeseries, get_activity_split_summaries, and get_activity_typed_splits also overlap enough that an agent could easily select the wrong one.

    Naming Consistency5/5

    The tool names follow a very consistent verb_noun pattern: nearly all reads are get_* and writes use preview_, create_, delete_, schedule_, unschedule_, and list_. All names are snake_case with predictable prefixes, making the naming style highly uniform across the entire set.

    Tool Count1/5

    63 tools is far beyond the 3-15 well-scoped range and well into the 50+ extreme-mismatch territory. While Garmin has a broad data surface, this many tools creates navigational overhead and many could be consolidated into parameterized or grouped endpoints.

    Completeness4/5

    The read surface is exhaustive, covering sleep, HRV, body battery, stress, activities, workouts, nutrition, menstrual data, and more. The write surface covers workout preview/create/list/schedule/unschedule/delete, with the main gap being no workout update or edit flow.

    Resources