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edxleon

runcoach

by edxleon
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Python
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Alternatives to runcoach

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    Related Servers

    • garmin-mcp

      cadencheng888
      F
      license
      Not graded
      quality
      D
      maintenance
      Connects Garmin watch data to Claude Desktop, allowing users to ask natural language questions about their health and activity data from Garmin Connect.
      -

    • garmin-mcp-server

      vnglst
      F
      license
      Not graded
      quality
      B
      maintenance
      Connects Claude Desktop to your Garmin Connect running data stored locally in SQLite, enabling querying, syncing, and AI analysis of fitness activities.
      1
      -

    • garmin-mcp

      Bartolome69
      A
      license
      A
      quality
      B
      maintenance
      Connects Claude to your Garmin Connect account to read activities, health metrics, and sleep data, and to create and schedule structured workouts directly onto your watch, all locally without exposing credentials.
      8
      2
      MIT

    • garmin-mcp

      mskerwiderski
      A
      license
      Not graded
      quality
      B
      maintenance
      Enables reading and analyzing Garmin Connect data—activities, health metrics, FIT files, and challenges—through natural language, for AI assistants like Claude and ChatGPT.
      MIT
    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

    A4.4/5.0

    Scored across 13 tools

    Disambiguation5/5

    Each tool serves a distinct purpose: specific metric retrievals (vo2max, trend, load, activities, intensity, daily, readiness, recovery), a workout deep-dive, two proposal generators, one apply action, and a sync function. There is no meaningful overlap; even similar 'get' tools focus on different data slices (e.g., single metric trend vs. multi-metric summary).

    Naming Consistency5/5

    All tool names follow a consistent snake_case pattern with a clear verb prefix (get_, sync_, analyze_, propose_, apply_) and a descriptive noun. The verbs map cleanly to actions (get for reads, propose for plans, apply for writes), making the API predictable and self-documenting.

    Tool Count5/5

    With 13 tools, the server covers the full coaching lifecycle without bloat. Each tool addresses a distinct piece of the workflow—data ingestion, metrics retrieval, analysis, planning, and execution—so the count feels appropriate for the stated domain.

    Completeness5/5

    The tool surface covers the entire coaching loop: syncing data, reading all key metrics and trends, analyzing individual workouts, generating single-session and weekly proposals, and applying them to Garmin. No obvious gaps exist for a personal coaching use case, including readiness and recovery checks that guide recommendations.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues

    Resources