A
licenseA
qualityB
maintenanceEnables 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.
4
9 npm
MIT
Intervals.icu MCP Server
by jakub-m-arch
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TDQS
A3.7/5.0
Scored across 36 tools
Disambiguation5/5
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.
Naming Consistency5/5
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.
Tool Count2/5
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.
Completeness3/5
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.
Maintenance
ActivityMaintained
ResponsivenessNo issues