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Strava MCP Server

by gcoombe
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    • Strava MCP Server

      juanlarreapm
      A
      license
      B
      quality
      D
      maintenance
      Integrates with the Strava API to allow AI assistants to access fitness data including athlete profiles, activity history, and segment statistics. It enables users to query detailed performance metrics and explore geographic segment data through natural language commands.
      8
      182 npm
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    • strava-mcp

      benniblau
      F
      license
      Not graded
      quality
      B
      maintenance
      Enables querying and analyzing personal Strava activity data through natural language, including activities, segments, gear, and training trends.
      -

    • Strava MCP Server

      LimeON-source
      A
      license
      B
      quality
      D
      maintenance
      Enables users to interact with their Strava data through natural language to analyze workouts, track fitness progress, and explore routes. It supports retrieving detailed activity stats, heart rate data, and segment insights directly within AI assistants.
      26
      312 npm
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    • Strava MCP Server

      KerkhofMe
      A
      license
      B
      quality
      D
      maintenance
      Connects Claude to the Strava API to provide direct access to fitness data, including athlete statistics, detailed activity logs, and time-series performance metrics. It enables users to analyze training progress, compare workouts, and retrieve specific segment details through natural language queries.
      8
      182 npm
      ISC
    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

    B3.3/5.0

    Scored across 22 tools

    Disambiguation5/5

    Every tool has a clearly distinct purpose targeting specific resources (activities, athlete, clubs, gear, routes, segments) and actions (get, create, update, delete, explore). There is no overlap or ambiguity between tools, making it easy for an agent to select the correct one.

    Naming Consistency5/5

    All tools follow a consistent verb_noun pattern (e.g., get_activity, create_activity, update_activity) with no deviations. The naming is uniform throughout, using snake_case and clear action-resource combinations.

    Tool Count4/5

    With 22 tools, the count is slightly high but reasonable for the Strava domain, which covers activities, athlete data, clubs, gear, routes, and segments. It provides comprehensive coverage without being excessive, though it borders on the heavy side.

    Completeness5/5

    The tool set offers complete CRUD/lifecycle coverage for key resources like activities (create, get, update, delete) and extensive read operations for athlete, clubs, gear, routes, and segments. There are no obvious gaps, supporting full agent workflows in the Strava ecosystem.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues

    Resources