Hyrox Coach MCP
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- AlicenseNot gradedqualityBmaintenanceEnables an AI agent to read Garmin sleep, readiness and activity data, build an athlete profile, check proposed sessions against code-enforced limits and real calendar availability, and then push approved structured workouts to a Garmin watch. Plans are proposed and stored under a plan ID, so only explicitly approved sessions are ever written.MIT
- AlicenseNot gradedqualityAmaintenanceEnables read-only access to WHOOP recovery, sleep, HRV, strain, workout, and race-performance data so assistants like Claude, Codex, and GitHub Copilot can answer personal health questions, compare trends against personal baselines, and audit HYROX or triathlon training with local, evidence-backed dashboards. Includes aggregate mode, local-only race logging, and verification tools for recomputing claims.12 npmMIT
- AlicenseNot gradedqualityAmaintenanceEnables users to query and analyze their WHOOP recovery, sleep, HRV, strain, workouts, and personal health data through AI assistants. It provides read-only access, local operation, and optional HYROX and triathlon tracking.12 npmMIT
- FlicenseNot gradedqualityAmaintenanceGrants AI assistants read-only access to your WHOOP recovery, sleep, HRV, strain, and workout history so you can ask natural-language questions about daily readiness, personal baselines, sleep debt, trends, and weekly reviews. It also rebuilds HYROX and triathlon sessions, tracks race load and readiness, and runs a local dashboard for auditing and correcting performance data.12 npm-
- AlicenseNot gradedqualityAmaintenanceEnables Claude, Codex, and GitHub Copilot to answer natural-language questions about WHOOP recovery, sleep, HRV, strain, and workouts using read-only access to personal health history, baselines, trends, and sleep debt. Also rebuilds HYROX and triathlon sessions, assesses race readiness, and serves a local performance dashboard.12 npmMIT
- AlicenseBqualityCmaintenanceTurns any AI assistant into a physiological AI running coach by abstracting fitness APIs and exposing 70+ structured analytical MCP tools based on endurance models.21MIT
TDQS
Scored across 9 tools
Each tool targets a distinct slice: readiness (daily recovery), coach_plan (upcoming runs), progress (long-term trends), training_summary (weekly load), sessions (recent log). There is mild overlap between get_progress and get_training_summary since both touch load/efficiency metrics, but descriptions make the split clear enough.
Consistent snake_case verb_noun pattern throughout: get_*, list_sessions, log_session_note, set_race_profile. The get/set pairing for race_profile is predictable and readable.
Nine tools is well-scoped for a hybrid-training coach. Each tool maps to a clear athlete-facing function with no filler.
The surface covers read paths across readiness, plan, progress, summaries and sessions, plus write paths for notes and race profile. Minor gaps: no explicit update/delete for logged session notes, and no way to remove or edit a race profile beyond overwrite-by-set.