MCP For Claude Marketplace
Strava Social

Strava Social MCP Connector for Claude

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Explore Strava activities feed, kudos, comments, clubs, and discover new segments.

10 tools Official Updated Jun 28, 2026 Official Vinkius Partner
More Details Connect to Claude

Connect Strava Social to any AI agent and explore the social side of Strava — activity feeds, kudos, comments, club memberships, and segment discovery.

What you can do

  • Activity Feed — Browse your recent activities with full details, kudos counts, and comment counts
  • Activity Comments — Read all comments on any activity with author names and text
  • Activity Kudos — See who liked/supports your activities with full athlete profiles
  • Athlete Profile — Get your Strava profile details including location, follower counts, and equipment
  • Club Membership — List all clubs you belong to with member counts and sport types
  • Club Details — Explore any club's description, location, and community focus
  • Club Members — Browse club membership to find training partners and local athletes
  • Club Activities — See what club members have been doing recently
  • Starred Segments — Review all your favorited segments with PR times and characteristics
  • Segment Discovery — Explore segments in any geographic area by bounding box, filterable by type and difficulty

How it works

  1. Subscribe to this server
  2. Enter your Strava Access Token (OAuth2)
  3. Start exploring your Strava social network from Claude, Cursor, or any MCP-compatible client

Who is this for?

  • Social Athletes — stay engaged with training partners, track kudos and community interaction
  • Club Organizers — monitor club activity levels, member engagement, and discover new training routes
  • Training Groups — explore what teammates are doing, find popular segments in your area
  • New City Explorers — discover popular cycling/running segments when traveling to new cities
activity-trackingsocial-networkingfitness-datacommunity-engagementsegment-discovery

10 tools expose this connector's capabilities to your AI agent.

list_activities

Activities are sorted by most recent first. Optional filters: "before" (epoch timestamp, defaults to now), "after" (epoch timestamp for date range), "page" and "per_page" (pagination, max 200 per page, max 2000 total). Each activity includes: name, type, distance, moving_time, elevation, kudos_count, comment_count, start_date, and basic stats. Use this to get the activity feed, analyze recent workouts, or review training history. Epoch timestamps can be generated from dates. List the authenticated athlete's activities with optional date filtering and pagination

get_athlete

Use this to understand the athlete's identity, location, and equipment setup. Get the authenticated athlete's profile information

get_club

The clubId is found in Strava club URLs. Use this to explore club details before joining or to understand a club's focus and community. Get detailed information about a specific Strava club

list_club_activities

Each entry includes athlete name, activity name, type, distance, and date. Paginated (30 per page). The clubId is from Strava club URLs. Use this to stay updated on club training activity, discover what members are doing, or find group workout opportunities. Get recent activities from members of a Strava club

list_club_members

Paginated (30 per page). The clubId is from Strava club URLs. Use this to discover training partners in a club, find athletes in your area, or explore club community composition. List members of a specific Strava club

list_athlete_clubs

Each club includes name, member count, city, country, sport type (cycling/running/triathlon), and privacy status. Use this to discover club memberships, find training groups, or understand community affiliations. List all clubs the authenticated athlete belongs to

get_activity_comments

Each comment includes athlete name, text, and creation date. The activityId is the numeric ID from Strava activity URLs. Use this to see community engagement on a workout, read feedback, or track conversation around a specific activity. Get all comments on a specific Strava activity

explore_segments

g., "-74.00,40.70,-73.95,40.75" for Manhattan). Optional filters: activity_type ("running" or "riding"), min_cat/max_cat (category 0-5, where 0 is hardest/steepest). Returns segments with name, distance, elevation, grade, and climb category. Use this to discover new training routes, find popular segments in an area, or plan rides/runs in a new city. Explore and discover Strava segments in a geographic area

get_activity_kudos

Each entry includes athlete name, profile picture, and city. The activityId is the numeric ID from Strava. Use this to see who supported an activity, understand social engagement, or track training partners' interactions. Get the list of athletes who gave kudos (likes) to a specific activity

list_starred_segments

Each segment includes: name, distance, elevation gain, average grade, activity type, city, country, and the athlete's PR time if any. Use this to review favorite segments, plan training routes, or track progress on key segments over time. List all segments starred (favorited) by the authenticated athlete

See how to talk to your AI agent using Strava Social.

Show my recent activities.

Recent activities: 1) Morning Ride — 45.2 km, 1h32m, 520m elev, 12 kudos. 2) Easy Run — 8.5 km, 42min, 85m elev, 8 kudos. 3) Recovery Ride — 22 km, 48min, 120m elev, 5 kudos. 4) Tempo Run — 10 km, 38min, 95m elev, 15 kudos.

Explore cycling segments in Manhattan, NYC.

Found 25 segments in Manhattan. Top climbs: 1) Cat 1 climb: West Side Highway (2.1 km, 4.2% avg) — 3,420 efforts. 2) Cat 3: Central Park North Hill (0.8 km, 8.1% avg) — 1,890 efforts. 3) Cat 4: Broadway Sprint (1.5 km, 2.1% avg) — 2,150 efforts. Most attempted: Central Park Full Loop (6.2 km).

Show comments on my latest activity.

Found 5 comments: 1) Sarah M.: "Great pace on that ride! 💪" 2) Tom K.: "Nice work! How did the new route feel?" 3) Lisa P.: "Solid effort 🚴" 4) Mike R.: "Let's do this route together next week" 5) Anna D.: "Impressive elevation gain!"

Yes! Use the get_activity_kudos tool with any activity ID. It returns the full list of athletes who gave kudos to that activity, including their names, cities, and profile pictures. This helps you understand who's following and supporting your training.

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