garmin-local-mcp
Related Servers
Alternatives to garmin-local-mcp
- AlicenseAqualityBmaintenanceFitness AI - MCP server providing AI-powered tools and automation by MEOK AI Labs59 npmMIT
- FlicenseBqualityCmaintenanceA personal remote MCP server for fitness data that provides read-only tools to query Garmin Connect activities and Hevy workouts, enabling users to list, retrieve, and analyze exercise records through natural language.13-
Related Servers
- FlicenseNot gradedqualityDmaintenanceA multi-platform fitness MCP server that syncs data from Garmin, Strava, Google Fit, and Suunto into a local DuckDB database and provides analytics tools via MCP.1-
- AlicenseNot gradedqualityAmaintenanceMCP server that mirrors your Garmin data into a personal database and exposes tools for health summaries, training load, muscle readiness, and race analysis, with optional chat-driven insights via stdio or HTTP.1MIT
- AlicenseBqualityAmaintenanceLocal-first MCP server that connects AI agents to your Garmin sleep, HRV, Body Battery, stress, training readiness and activities, keeping tokens on your machine.242125 npm13MIT
- AlicenseNot gradedqualityCmaintenanceA local MCP server that exposes your Garmin Connect data—sleep, HRV, training readiness, workouts, and more—to any MCP-compatible AI assistant. Runs entirely on your machine and keeps your Garmin credentials private.MIT
- AlicenseBqualityAmaintenanceMCP server for local fitness-data extraction and analysis from Garmin Connect, Intervals.icu, and Strava. Provides read-only analytical tools over DuckDB and targeted Strava enrichment.35121 npmAGPL 3.0
- AlicenseAqualityBmaintenanceA local MCP server that caches Garmin Connect data in SQLite for fast, read-only queries, with tools for bulk import, rate-limited sync, and failure alerts.91MIT
TDQS
Scored across 13 tools
Each tool has a clearly distinct purpose, with explicit cross-references in descriptions guiding correct selection (e.g., circadian points to baselines/get_day for normalcy and correlate for relationships). No two tools overlap enough to cause misselection; even closely related tools like sync_status and gaps are differentiated by their focus (coverage/errors vs missing days/holes).
All names use snake_case, which is consistent, but the structural convention varies: some are bare nouns (circadian, baselines, anomalies, gaps), some are verb_noun (get_day, get_activity, query_metrics, list_activities), and others are status or action verbs (auth_status, sync, correlate). This mixed pattern is readable but lacks a predictable verb_noun scheme throughout.
13 tools is well within the ideal 3-15 range and each tool earns its place, covering distinct facets of local Garmin data handling: ingestion, status, retrieval, and analysis. The set is neither bloated nor thin for the domain.
The surface covers the essential lifecycle: sync/auth, coverage checks, day-level and activity-level retrieval, time-series queries, and multiple analysis tools (correlation, baselines, anomalies, circadian). Minor gaps exist, such as no explicit tool to discover available metric names for query_metrics, and activity detail is limited to summary rows (no streams), but these are workable limitations rather than dead ends.