Strava Alternative MCP for AI. Pull raw metrics and analyze performance without the mobile app.

You connect this server to your AI agent and treat every single run, ride, and segment you've done like pure data. You don't gotta dig through dashboards or mess with a mobile app; your agent pulls exactly what you need from your training history.

Analyzing Your Performance Metrics

You can pull detailed profile stats using get_athlete_stats to get an overview of your performance and profile details. For specific zone analysis, you've got get_activity_zones, which pulls the exact heart rate or power zones recorded during one activity. You can also check out your personal definition of zones with get_athlete_zones.

If you wanna keep basic tabs on yourself, get_authenticated_athlete grabs core details about the account linked to the server. To manage your profile info itself, use update_athlete; it lets you update basic details for your authenticated athlete account.

Managing Activities and Laps

To start analyzing, you'll first need a list of activities; list_athlete_activities shows you recent sessions so you can pick one up. Once you select an activity ID, get_activity pulls the main details for that specific session. If you want to change something about it—maybe fix a title or update the description—you use update_activity.

For deep-dive data, get_activity_streams fetches raw, high-resolution data streams for the entire activity session. Need to know exactly how often you stopped? list_activity_laps gives you a detailed list of measured laps from any recorded run or ride.

Community engagement is right there too. You can use list_activity_comments to see every comment someone left on an activity, and list_activity_kudos tells you which usernames gave kudos to it. You'll also find that if your agent needs to analyze the raw data for a whole route path, get_activity_streams does the heavy lifting.

Exploring Routes, Segments, and Efforts

Finding specific parts of your training is key. To search for segments based on where you are, use explore_segments, passing in geographic boundaries (bounds) to narrow down results. Once you find a segment, get_segment gives you all the detailed info about it (like 'Main Street Climb'). You can also check out every recorded effort made by any athlete on that segment using list_segment_efforts.

If you want raw data streams for a specific segment's effort over time, use get_segment_effort_streams; for general performance tracking on any segment, run get_segment_streams. To get the core details of a full route—the start/end points and distance—use get_route. You can also list all saved routes associated with you using list_athlete_routes, or if you've got favorites, list_starred_segments pulls that list.

Remember, you can mark or unmark any segment as a favorite using star_segment. When it comes to exporting data, you've got two options: export_route_gpx exports the route data in GPX format, and export_route_tcx does the same thing but uses TCX. If you need raw data streams for an entire route path—not just a segment—run get_route_streams.

Tracking Clubs and Community Data

For connecting with your crew, you can list all clubs you belong to using list_athlete_clubs. From there, get_club pulls detailed information for any specific club. If you wanna see the whole squad, use list_club_members to get a full roster of people in that club. You can also find who runs things with list_club_admins, or see all activities posted by members using list_club_activities.

You'll even get a list of all activities posted by other members within a specific club using list_club_activities.