Intervals.icu MCP Server
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Alternatives to Intervals.icu MCP Server
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- AlicenseAqualityBmaintenanceEnables AI assistants to read your Strava training data and answer plain-language questions about activities, splits, and totals across sports like running, skiing, and hiking.411 npmMIT
- AlicenseAqualityDmaintenanceEnables AI assistants to directly access and analyze Strava activity data, including runs, rides, and swims, through natural language queries.45 npmMIT
- AlicenseNot gradedqualityBmaintenanceEnables AI assistants to read Garmin activities and create/schedule structured workouts and multi-week training plans on Garmin Connect, syncing to the user's watch.1MIT
- AlicenseAqualityBmaintenanceProvides AI assistants with read-only access to an athlete's Intervals.icu training data, including activities, wellness metrics, zones, and planned events, for use with MCP clients like ChatGPT and Claude.15MIT
- AlicenseCqualityCmaintenanceEnables AI agents to read training data and, with explicit approval, replace planned workouts in a user's Intervals.icu account.7Apache 2.0
- AlicenseBqualityDmaintenanceEnables users to interact with their Strava data through natural language to analyze workouts, track fitness progress, and explore routes. It supports retrieving detailed activity stats, heart rate data, and segment insights directly within AI assistants.26312 npmMIT
TDQS
Scored across 36 tools
Each tool targets a distinct resource and action: list/search/get/update on activities, calendar events, and library workouts are clearly separated, and the analytics tools (streams, histogram, best efforts, segment stats) each have unique outputs. Even near-pairs like create_events vs create_workouts and create_manual_activity vs mark_event_done are disambiguated by their descriptions.
Tool names follow a consistent snake_case verb_noun pattern (list_*, get_*, create_*, update_*, duplicate_*), with only minor multi-word variants like mark_event_done and add_gear_reminder that remain predictable. The naming convention makes it easy to anticipate what each tool does.
36 tools is beyond the 25+ threshold for 'too many' in the calibration, making this a heavy tool set even though the server covers a broad training platform. Many tools are narrow and could be consolidated (e.g. activity analytics) or omitted for a more focused MCP surface.
The set covers most core workflows across athlete profile, activities, calendar planning, workout library, wellness, and gear, with read/create/update operations for most resources. However, there are no delete tools for activities, events, workouts, or folders, leaving lifecycle dead ends and making the CRUD coverage incomplete.