aimharder-mcp
Related Servers
Alternatives to aimharder-mcp
No user-submitted related servers found.
Related Servers
- AlicenseNot gradedqualityCmaintenanceEnables querying a Tonal fitness account for workout history with per-set weights, muscle readiness, strength scores, and lifetime stats through a remote MCP endpoint.MIT
- AlicenseNot gradedqualityBmaintenanceEnables MCP clients to connect to a privacy-first, self-hostable workout planning and training log, allowing coaching agents to preview and apply program changes while accessing training data through OAuth-protected endpoints.AGPL 3.0
- AlicenseNot gradedqualityBmaintenanceConnects MCP clients to Garmin Connect data, enabling queries about activities, sleep, heart rate, body battery, and training status.1MIT
- FlicenseAqualityDmaintenanceAllows for management of TrainHeroic Athlete accounts via MCP and the unofficial API20-
- AlicenseNot gradedqualityBmaintenanceEnables MCP clients to access and manage Intervals.icu training data, including activities, calendar events, wellness metrics, power curves, gear, and custom items, with zero-config interactive authentication.26 npmMIT
- AlicenseNot gradedqualityDmaintenanceRead-only MCP server for searching, comparing, and recommending UK gyms using the public LocalGym Agent API.52 npm1MIT
TDQS
Scored across 18 tools
Most tools have clearly distinct purposes, and the prepare/execute pairs for bookings and activities are well separated by intent. The main risk is the cluster of find_exercise_1rm, get_exercise_1rm, and get_exercise_rm_progression, which all touch 1RM data and could be confused despite differing scopes (search vs known ID vs progression series).
Names follow a predictable verb_noun snake_case convention (get_*, prepare_*, execute_*, find_*), with the prepare/execute two-phase pattern applied consistently across bookings and activities. Minor deviation: 'find_exercise_1rm' uses a different verb than the otherwise dominant get_* reads, creating a slight inconsistency.
18 tools is on the heavier side but each appears to earn its place across distinct domains (bookings, activities, workouts, 1RM reads). The count is justified by the two-phase prepare/execute plus late-cancellation flow, though it sits just above the ideal 3-15 range.
The surface covers booking creation, cancellation, late cancellation, upcoming/history reads, activity publication/deletion, and personal activity and 1RM retrieval. Coverage is broad and lifecycle-complete for core workflows; minor gaps exist (no explicit waitlist join, no profile/account mutation), but agents can work around them.