{"repo":"revo2wheels/intervalsicugptcoach-public","free":true,"listed":false,"github":"https://github.com/revo2wheels/intervalsicugptcoach-public","clone":"git clone https://github.com/revo2wheels/intervalsicugptcoach-public.git","description":"Deterministic endurance coaching engine using Intervals.icu data, governed training logic, performance intelligence, adaptation progression and AI interfaces.","language":"Python","stars":46,"topics":["ai","coaching","cycling","endurance-training","intervals-icu","mcp","performance-analysis","physiology","python","sports-science"],"license":"MIT","category":"mcp-servers","readme_excerpt":"Montis.icu Data access is not coaching intelligence. Montis.icu is a deterministic endurance coaching engine built around Intervals.icu data. It validates athlete evidence, resolves physiological and training context through explicit coaching logic, and produces a governed coaching state before conversational AI enters the dialogue. Intervals.icu → Montis intelligence → governed athlete state / decision → AI dialogue A direct API or MCP connection can expose useful athlete data. Montis adds the missing intelligence layer: longitudinal context, validation, performance behaviour, adaptation progression, phase/event governance and deterministic decision logic. Core principle Montis controls the coaching intelligence. AI explains and discusses the result — it does not independently invent the athlete's training state or coaching decision. The language model is downstream of the engine. It receives governed semantic output and turns that result into useful conversation across supported interfaces. Current architecture Execution entry points - Railway: app.py is the backend service entry point and dispatches into audit core/report controller.py . - Local CLI: report.py is the local report execution entry point. It obtains a prefetched dataset through Cloudflare Edge, then runs the Montis coaching engine locally through audit core/report controller.py . - Canonical controller: audit core/report controller.py executes the deterministic audit and intelligence chain. app.py imports run","default_branch":null,"files":null,"tree":[],"storefront":"/r/revo2wheels","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/revo2wheels/intervalsicugptcoach-public/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}