Intervals.icu MCP Server
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Alternatives to Intervals.icu MCP Server
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- FlicenseAqualityDmaintenanceEnables AI assistants to access and analyze intervals.icu training data including activities, fitness metrics (CTL/ATL/TSB), wellness stats, and calendar events. Supports natural language querying of athletic performance for training insights and workout planning.6-
- AlicenseAqualityDmaintenanceEnables interaction with Intervals.icu data, including activities, wellness, and calendar events, via natural language.1016 npm1MIT
- AlicenseNot gradedqualityCmaintenanceEnables Claude and ChatGPT to access and manage Intervals.icu data, including activities, events, wellness metrics, power curves, and custom items through natural language.GPL 3.0
- AlicenseAqualityCmaintenanceEnables Claude and ChatGPT to retrieve and manage activities, intervals, events, wellness data, power curves, and custom items through the Intervals.icu API.21GPL 3.0
- AlicenseNot gradedqualityCmaintenanceEnables Claude AI to access and manage intervals.icu training data, including workouts, wellness, and fitness trends, through natural language conversation.MIT
- AlicenseNot gradedqualityBmaintenanceConnects to Intervals.icu to let users query training data, create workouts, manage calendar events, and coach athletes through natural language in Claude Desktop.19 npmMIT
TDQS
Scored across 4 tools
Each tool has a clearly distinct purpose with no overlap: get_activities retrieves individual activity records, get_grouped_activities provides aggregated activity summaries, get_wellness fetches individual wellness metrics, and get_grouped_wellness offers aggregated wellness trends. The descriptions explicitly differentiate between individual data retrieval and grouped analysis for both domains.
All tools follow a perfectly consistent verb_noun pattern with clear prefixes: get_activities, get_grouped_activities, get_wellness, get_grouped_wellness. The naming convention is uniform throughout, using snake_case consistently and maintaining parallel structure between activity and wellness domains.
Four tools is reasonable for a fitness/wellness data server, covering the core domains of activities and wellness with both individual and grouped variants. However, the count feels slightly minimal - there might be room for additional operations like creating or updating records, though the current set adequately serves basic retrieval and analysis needs.
The toolset provides excellent read/analysis coverage for activities and wellness data, but lacks any write operations (create, update, delete). For a fitness tracking platform where users might want to log new activities or update wellness metrics, this represents a notable gap. The surface is complete for retrieval and analysis but incomplete for full CRUD lifecycle management.