Strava MCP Server
Related Servers
Alternatives to Strava MCP Server
No user-submitted related servers found.
Related Servers
- FlicenseAqualityDmaintenanceConnects Claude to your Strava fitness data, enabling natural language queries about your training history such as activities, stats, and routes.8-
- AlicenseAqualityDmaintenanceConnects Claude to your Strava account for analyzing training, predicting race times, and generating periodized training plans via natural language.13182 npmISC
- AlicenseAqualityDmaintenanceConnects Claude to your Strava account so you can query your activities, stats, routes, and segments using natural language.277 npm1MIT
- FlicenseNot gradedqualityDmaintenanceEnables Claude to access and analyze your Strava activities through OAuth authentication. Supports retrieving activity lists and detailed workout data for fitness tracking and analysis.2-
- AlicenseAqualityDmaintenanceConnects Strava training data to Claude, enabling personalized coaching through analysis of training load, workout planning, gear maintenance, and power metrics.1023 PyPIMIT
- AlicenseNot gradedqualityCmaintenanceConnects Claude to Strava data for natural language queries about rides, stats, and activities.11 npmMIT
TDQS
Scored across 8 tools
Each tool has a clearly distinct purpose targeting specific Strava resources: activities (list, range, detail, streams), athlete (profile, stats), and segments (detail, starred). No overlap exists in functionality, making tool selection unambiguous for an agent.
All tools follow a consistent verb_noun pattern with 'get_' prefix and descriptive suffixes (e.g., get_activities, get_activity_streams). This predictable naming convention enhances readability and agent usability throughout the set.
With 8 tools, this server is well-scoped for the Strava domain, covering core resources like activities, athlete data, and segments. Each tool earns its place by addressing distinct aspects of the API without being overwhelming or insufficient.
The tool set provides strong read-only coverage for activities, athlete, and segments, but lacks write operations (e.g., create/update activities, star segments) or broader functionality like clubs or routes. This is a notable gap that may limit agent workflows requiring full CRUD capabilities.