Intervals MCP
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Related Servers
- 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.1017 npm1MIT
- AlicenseNot gradedqualityBmaintenanceEnables a single owner to query their intervals.icu training data — athlete profile and recent activities — from ChatGPT through an OAuth-protected, read-only connection. It authenticates the owner via GitHub sign-in and exposes a read-only toolset with no write, delete, or coach capabilities.Apache 2.0
- AlicenseNot gradedqualityCmaintenanceConnects to Intervals.icu to let users query training data, create workouts, manage calendar events, and coach athletes through natural language in Claude Desktop.139 npmMIT
- FlicenseAqualityDmaintenanceEnables AI assistants to interact with Intervals.icu fitness tracking and wellness data, allowing users to fetch, filter, and group activities or health metrics. It provides structured summaries of workouts and physical well-being through natural language queries.4-
- AlicenseNot gradedqualityNot gradedmaintenanceEnables Claude to read recent training and wellness data and create, update, or delete structured workouts on an intervals.icu calendar that syncs to Garmin Connect and the user's watch.MIT
TDQS
Scored across 5 tools
Each tool targets a distinct resource-action pair: athlete, activities, wellness, and events, with list versus get clearly separating collection from detail operations. An agent would not struggle to pick among them.
All tool names consistently follow a resource_verb pattern in snake_case, with plural resources for list operations and singular resources for detail operations. There are no stylistic deviations or ambiguous verbs.
Five tools is a compact, well-scoped set for a read-only fitness data server. Each tool covers a meaningful endpoint with no redundancy or bloat.
The surface covers core read workflows: athlete profile, activity list/detail, wellness records, and calendar events. It lacks write operations and detail endpoints for wellness/events, but these are likely outside the read-only scope and list results may be sufficient.