A
licenseA
qualityD
maintenanceEnables AI assistants to directly access and analyze Strava activity data, including runs, rides, and swims, through natural language queries.
4
17 npm
MIT
Strava MCP Server
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- FlicenseNot gradedqualityBmaintenanceEnables querying and analyzing personal Strava activity data through natural language, including activities, segments, gear, and training trends.-
- AlicenseNot gradedqualityCmaintenanceGives 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
TDQS
B3.4/5.0
Scored across 26 tools
Disambiguation4/5
Most tools have distinct purposes targeting specific Strava resources (e.g., activities, segments, routes, athlete data), with clear separation between get, list, and action operations. However, some potential overlap exists between 'get-all-activities' and 'get-recent-activities', and between 'explore-segments' and 'list-starred-segments', which could cause minor confusion in selection.
Naming Consistency3/5
Naming conventions are mixed, with most tools using kebab-case (e.g., 'get-activity-details') but some using snake_case (e.g., 'get_athlete_stats' in the description). Verb patterns vary, including 'get-', 'list-', 'export-', 'check-', 'connect-', 'disconnect-', 'explore-', and 'star-', which reduces predictability. While readable, the inconsistency across styles and verbs lowers the score.
Tool Count3/5
With 26 tools, the count is borderline high for a Strava integration, suggesting potential over-scoping. While Strava's API is feature-rich, this many tools might overwhelm agents or indicate fragmentation. A more focused set of 15-20 tools could improve coherence without sacrificing functionality.
Completeness5/5
The tool set provides comprehensive coverage of the Strava domain, including athlete management (connect, profile, stats, zones), activities (details, laps, photos, streams, lists), segments (explore, get, leaderboard, efforts, starring), routes (get, export), and clubs. It supports full CRUD-like operations where applicable (e.g., connect/disconnect, star/unstar) and handles key workflows like data export and analysis, with no obvious gaps.
Maintenance
ActivityInactive
ResponsivenessNo issues