Intervals.icu MCP Server

Overview

The Intervals.icu MCP Server bridges Claude and the Intervals.icu API, allowing AI assistants to pull authenticated athlete data directly into conversational workflows. By exposing a set of high‑level tools—such as , , and —the server eliminates the need for developers to write custom API wrappers or manage OAuth flows. Instead, they can rely on MCP’s declarative tool specification to request structured data and receive JSON responses that Claude can interpret or transform on the fly.

For developers building training analytics, coaching dashboards, or personalized workout recommendations, this server solves a common pain point: accessing time‑series activity and wellness information without exposing raw credentials. The server authenticates once using an API key and athlete ID, then caches requests to respect Intervals.icu’s rate limits while still delivering up‑to‑date insights. The result is a secure, repeatable interface that fits neatly into existing AI pipelines.

Key capabilities include:

• Authentication abstraction – The server handles API key storage and request signing, freeing developers from boilerplate code.
• Structured data retrieval – Tools return clean JSON payloads for activities, intervals, events, and wellness metrics, enabling Claude to summarize trends or flag anomalies.
• Event awareness – and let AI assistants anticipate upcoming races or training sessions, facilitating proactive coaching prompts.
• Interval granularity – exposes split‑level data, useful for performance analysis or biomechanical modeling.

Typical use cases span from personal training assistants that can say, “Show me my last 30‑minute interval times,” to coaching platforms that automatically generate weekly performance reports. In a workflow, a developer might configure Claude Desktop with the MCP server, then write prompts that call to list recent workouts, followed by to correlate sleep quality with performance. The server’s tight integration ensures low latency and consistent data formatting, which is crucial for real‑time coaching scenarios.

What sets this MCP Server apart is its minimal configuration footprint and direct alignment with Intervals.icu’s native data structures. Developers can focus on higher‑level logic—such as trend detection or recommendation engines—while the server guarantees reliable, authenticated access to a rich dataset. This synergy makes it an attractive component for any AI‑powered sports analytics stack that relies on Intervals.icu as the source of truth.