TrainingPeaks MCP server for Claude Desktop, Code and Cowork. No API approval needed - works with any account. Query workouts, CTL/ATL/TSB fitness data, power PRs via natural language.
Evidence-based AI coach for endurance training. Protocol-driven. Deterministic guidance for any LLM, with Intervals.icu integration.
🏃 An R package for advanced sports performance analysis and training load monitoring using Strava data.
The open-source European alternative to TrainingPeaks. Self-hostable endurance training platform. Your data stays yours.
Own your training data! Open-source, self-hosted training log & analytics. Calendar, fitness/fatigue/form, dashboards, zones, peak curves & intervals.icu sync.
Local MCP server exposing your Intervals.icu training data to AI clients (Claude, etc.) — with server-side PMC / cardiac-decoupling math and a Stryd LBSS power extension.
🏋️♂️ Connect TrainingPeaks to AI assistants with ease. Query workouts, analyze data, and track fitness trends without API approval hassles.
Daily training-readiness score from Intervals.icu wellness data, pushed to your calendar.
Local, self-hosted training log with Garmin sync, fitness/training-load analytics, and an AI coach: fart (speed) + lek (play).
Interpreting wearable fitness data through a physiology lens: HRV, VO2 max estimation, sleep tracking accuracy, training load metrics, and device validation studies.
Este repositorio recoge el código para el proyecto Trail Analytics: Exploración visual y modelado predictivo de carreras por montaña.
Evidence-based Claude Code skill: Garmin FR570 → 4-tier daily training decision + 8-KPI weekly fat-loss review. 206 citations, deterministic decision tree, anti-overreach red lines.
Curated research on training periodization: linear, undulating, block, conjugate, and polarized models. Tapering science, training load monitoring, and individualization evidence.
The open-source engine behind journeytoironman.app — Strava + Apple Health to Postgres, sports-science KPIs (CTL/ATL/TSB, EF, ACWR), 16-week 70.3 plan, local + Databricks dashboards.
I killed my SaaS and rebuilt it as a skill — an AI-native training copilot that crosses your objective load with how you actually feel, on your own AI (Claude / OpenClaw). It reads, you decide. Zero infra.
Vendor-neutral, local-first and auditable sports and recovery trends with deterministic metrics and an evidence-gated AI coach core.
Self-hosted cycling coach with a local LLM that never makes up a number — training load, overtraining detection & grounded AI advice.
Local-first training intelligence for trail running: COROS ingestion, load and recovery metrics, guarded daily recommendations, and grade-adjusted GPX pacing plans.
Daily Coros Training Hub briefing as JSON — readiness, HRV, training load, activities, plan
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