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nitinchakravarthy

Workout Tracker MCP Server

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    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables conversational logging and retrieval of workouts, sets, weigh-ins, meals, goals, plans, and progress photos through MCP-capable AI clients, with authenticated per-user storage and export/query capabilities.
      ISC
    • A
      license
      Not graded
      quality
      D
      maintenance
      A comprehensive AI-powered fitness tracking application that enables AI tools to interact intelligently with user fitness data, providing personalized workout plans, nutrition tracking, and progress analysis through natural language.
      15
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables AI assistants to plan, build, and log calisthenics workouts in a user's own account, including searching exercises, managing custom workouts and plans, reading progress and coaching data, and logging completed sessions. Account mutations require explicit confirmation, and workouts can be displayed as interactive cards in the chat.
      MIT
    • F
      license
      Not graded
      quality
      D
      maintenance
      Enables workout tracking and coaching within Claude conversations, managing exercise configs, logs, streaks, and health metrics via an MCP server with PostgreSQL.
      -
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables AI assistants and native clients to manage training plans, workout history, reusable recipes, meal records, and media through validated, versioned MCP and REST operations. It stores and validates structured fitness and nutrition data, including nutrition calculation, food catalog lookup, and Apple Health export status.
      MIT

    TDQS

    A3.5/5.0

    Scored across 14 tools

    Disambiguation2/5

    log_workout and log_workout_session_to_dynamodb both log workouts but at different levels of detail and persistence, creating real ambiguity for an agent. The multiple get_exercises_by_* filters are largely distinct but could be confused with search_exercises, especially since they all return exercise lists.

    Naming Consistency4/5

    Tool names consistently use snake_case with a verb_noun pattern, such as list_*, get_*, log_*, and save_*. Minor deviations like calculate_volume (no resource object) and the long 'to_dynamodb'/'from_dynamodb' suffixes are still readable and predictable.

    Tool Count4/5

    With 14 tools, the count is on the higher end but still within a reasonable scope for an exercise database combined with workout plan and session logging. A few tools, especially the redundant log_workout, could be consolidated, but the overall count is not excessive.

    Completeness2/5

    The server provides save/get for workout plans and a session logger, but lacks list, update, and delete operations for plans or logs. There is also no way to retrieve a user's workout history, leaving significant lifecycle gaps that would cause agent failures in common tracking workflows.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues