intervals-icu-sync
Active·★ 21·MIT·Updated 2026-10-21
This project provides tools to fetch, analyze, and export cycling training data from intervals.icu, integrating with AI assistants for personalized coaching. It supports both local script execution and a hosted Model Context Protocol (MCP) server for direct AI assistant connection to manage training plans.
#Cycling Analytics#AI Coaching#Training Data#LLM Integration#intervals.icu API#Data Processing#Workflow Automation#Python
01
Features
01Fetch and analyze cycling training data from intervals.icu.
02Integrate with AI assistants (e.g., ChatGPT, Claude) using specialized system prompts and a coaching logic library.
03Upload AI-generated structured training plans directly to the intervals.icu calendar.
04Perform comprehensive training quality, carbohydrate fueling, and performance metrics (FTP, VO2Max, HRV) analysis.
05Offers flexible deployment options: local Python scripts or a managed Model Context Protocol (MCP) server.
02
Compatibility
Python
Runtime
Verified via docs
intervals.icu API
Data Source
Verified via docs
LLMs (ChatGPT, Claude, Copilot)
AI Assistant
Verified via docs
Microsoft Foundry
Agent Platform
Verified via docs
Azure App Service
Deployment Target
Verified via docs
03
Quick start
1
$ python -m venv .venv
2
$ source .venv/bin/activate
3
$ pip install -r requirements.txt
04
Use cases
↳Automate weekly analysis of cycling training data and athletic performance for cyclists.
↳Receive personalized, AI-generated training plans directly uploaded to the intervals.icu calendar.
↳Integrate custom AI coaching solutions with rich intervals.icu activity and wellness data.
↳Evaluate carbohydrate fueling strategies per session and get recommendations for future rides.
↳Track and interpret key performance metrics, fatigue levels, and form to optimize training.
05
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