MCP server for Intervals.icu β access training, wellness, and performance data from LLMs.
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β or use 1-click editor setup below.
π‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

A Model Context Protocol (MCP) server for Intervals.icu integration. Access your training data, wellness metrics, and performance analysis through Claude, ChatGPT, and other LLMs.
Originally based on eddmann/intervals-icu-mcp (MIT licensed). This project is an independent continuation with significant bug fixes and new features β see CHANGELOG.md for details.
62 tools spanning activities, activity analysis, activity messages, athlete profile, wellness, events/calendar, performance curves, workout library, gear, sport settings, and custom items β plus 4 MCP Resources (athlete profile, workout syntax, event categories, custom item schemas) and 7 MCP Prompts (training analysis, recovery check, weekly planning, and more). See Available Tools for the per-category breakdown.
Or for Claude Desktop, in 30 seconds:
Prefer Claude Code, Cursor, or ChatGPT? See Client Configuration. Want to run from source or with Docker? See Installation & Setup.
Install uv β it handles Python, dependencies, and execution in one tool. brew install uv on macOS/Linux, or powershell -c "irm https://astral.sh/uv/install.ps1 | iex" on Windows. From there, uvx fetches Python and the package automatically. Docker is also supported as an alternative.
Before installation, obtain your Intervals.icu API key:
i123456).Nothing to install separately if you use the recommended setup. uvx (which ships with uv) automatically downloads and caches the intervals-icu-mcp package the first time your MCP client launches it β just paste the config snippet from Client Configuration into your client and you're done.
Then point your MCP client at this checkout β see the From source snippet inside each client below.
Or create intervals-icu-mcp.env manually (same format as the .env above).
Then point your MCP client at the Docker image β see the Docker snippet inside each client below.
The server speaks MCP over stdio and works with any compliant client. Click a client to expand. If you followed Quick Start (uvx), use the first config block; if you used the source or Docker alternative above, use the matching variant inside the same collapsible.
Add to your configuration file:
~/Library/Application Support/Claude/claude_desktop_config.json%APPDATA%\Claude\claude_desktop_config.jsonFrom source (requires git clone + uv sync + uv run intervals-icu-mcp-auth):
Docker:
Register the server as a user-scoped MCP server:
Then in any Claude Code session, run /mcp to confirm intervals-icu is connected.
Add to ~/.cursor/mcp.json (or the project-local .cursor/mcp.json):
Restart Cursor and open Settings β MCP to verify the server is listed.
ChatGPT's custom MCP connector flow requires running the server over HTTP and exposing it via a tunnel, then registering the URL in ChatGPT's Developer Mode settings. See docs/chatgpt-connector.md for the full walkthrough, plan-tier requirements, and security notes.
Ask Claude to interact with your Intervals.icu data in natural language. A few starter prompts:
For the full catalogue of example prompts by category, see docs/examples.md.
62 tools, 4 resources, and 7 prompt templates. One-line summary below β full reference in docs/tools.md.
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