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strava-mcp

by KalleStalhandske
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    • 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
      206 npm
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    • SportMCP

      vivekvy-run
      A
      license
      Not graded
      quality
      C
      maintenance
      Gives any MCP-compatible AI assistant secure, read-only access to your personal Strava fitness data, including activities, segments, routes, gear, and more through natural language.
      MIT

    • Strava MCP Server

      esowder22
      A
      license
      A
      quality
      C
      maintenance
      Enables Claude to access your personal Strava data read-only, including activities, splits, heart-rate and pace streams, zones, and lifetime totals, so it can coach from real training without manual exports.
      6
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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
      43 npm
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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

    A4.4/5.0

    Scored across 4 tools

    Disambiguation5/5

    Each tool targets a distinct resource: athlete profile, recent activity list, individual activity details, and athlete stats. The descriptions cross-reference each other clearly (e.g., using get_recent_activities to find IDs for get_activity_details), eliminating ambiguity.

    Naming Consistency5/5

    All tool names follow a consistent get_<noun> pattern, using snake_case throughout. The naming clearly distinguishes list/detail operations without introducing mixed conventions or vague verbs.

    Tool Count4/5

    Four tools is a compact but reasonable set for a read-only Strava personal data server. While slightly small, the count is appropriate for the focused scope and each tool covers a necessary data retrieval need.

    Completeness4/5

    The server covers the core personal data lifecycle: profile, stats, activity list, and activity details. It lacks streams/segments or social features, but these are not obvious gaps for the described purpose of retrieving an athlete's summary data.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues

    Resources