intervals-mcp

intervals-mcp

Provides AI assistants with read-only access to an athlete's Intervals.icu training data, including activities, wellness metrics, zones, and planned events, for use with MCP clients like ChatGPT and Claude.

Category
Visit Server

README

Intervals MCP

Русская версия

A self-hosted, read-only MCP server that gives AI assistants access to an athlete's Intervals.icu training data.

Connect a sports watch, bike computer, trainer, Strava, or another supported source to Intervals.icu. Intervals MCP then exposes the normalized training data to ChatGPT, Claude, Claude Code, Cursor, VS Code, and other MCP clients. See Intervals.icu for its current integrations; the list changes over time.

The server only makes GET requests. It cannot create, edit, or delete anything in an athlete's Intervals.icu account.

What an assistant can read

  • Athlete profile, timezone, sport settings, zones, FTP, LTHR, and max HR.
  • Activities, details, laps, intervals, and downsampled streams.
  • Wellness, fitness, fatigue, HRV, sleep, mood, and weight when available.
  • Planned events, best-effort curves, gear, and the workout library.
  • Additional Intervals.icu v1 GET endpoints through a read-only raw tool.

Large responses are compacted before they reach the model. Empty fields are dropped, streams are downsampled, and summaries use the full data series.

Quick start

You need an Ubuntu or Debian VPS with a public hostname. Point the hostname's DNS record at the server and allow inbound TCP ports 80 and 443. The installer adds Docker, Compose, Git, and uv when they are missing:

curl -fsSL https://raw.githubusercontent.com/VictorForV/intervals-mcp/master/install.sh | sudo bash

Review install.sh before running it if you prefer not to pipe a remote script to a privileged shell. Manual installation remains available by cloning the repository and running ./manage.sh after installing the prerequisites.

Choose Initial setup. The manager asks for the public hostname, a short athlete name, and the Intervals.icu athlete ID and API key. The ID and key are available under Settings → Developer Settings in Intervals.icu. The API key uses hidden input.

The manager creates owner-only configuration, generates a strong random URL token, starts the service, and prints the connector URLs. Run ./manage.sh later to add, list, edit, or remove athletes, rotate URLs, rebuild, restart, or inspect the service.

Connecting an AI client

Each athlete receives two secret URLs:

https://mcp.example.com/<secret>/mcp  # Streamable HTTP, preferred
https://mcp.example.com/<secret>/sse  # legacy SSE compatibility

Treat the complete URL like a password. It grants read access to that athlete's training and wellness data.

Claude and Claude Desktop

Open Settings → Connectors → Add custom connector and enter the /mcp URL. Availability and organization permissions depend on the Claude plan. See the current Anthropic instructions.

Claude Code

The manager prints a ready-to-run command:

claude mcp add --transport http intervals-alex https://mcp.example.com/<secret>/mcp

ChatGPT

Add the server as a custom app/connector and use the URL accepted by your current ChatGPT workspace. Availability, UI, and administrator requirements vary by plan and can change. See the current OpenAI apps documentation. The manager shows both URL formats for compatibility.

Other clients

Use /mcp with remote Streamable HTTP clients and /sse with older SSE clients. Follow the client's current documentation and never commit a secret URL to a shared configuration.

Administration

The interactive panel is the recommended interface:

./manage.sh

For automation, the same interface has subcommands:

uv run intervals-mcp-admin add
uv run intervals-mcp-admin list
uv run intervals-mcp-admin show alex
uv run intervals-mcp-admin edit alex
uv run intervals-mcp-admin rotate alex
uv run intervals-mcp-admin remove alex

Avoid --api-key in an interactive shell because command arguments can be saved in shell history or exposed in the process list. Omit it for hidden input.

Local stdio mode

For one athlete and a client that launches local processes, copy .env.example to .env, configure the Intervals.icu credentials, and run:

uv run intervals-mcp

Security model

  • Intervals.icu requests are read-only (GET).
  • Each athlete gets a separate API client and independent random path token.
  • .env and users.toml are gitignored and written with mode 0600.
  • API keys and path tokens are excluded from application and proxy access logs.
  • The public service uses HTTPS through Caddy.
  • users.toml is mounted read-only into the container.

The path token is bearer authentication: anyone with the URL can read that athlete's data. Rotate it from ./manage.sh if exposed. See SECURITY.md for reporting issues.

Development

uv sync
uv run pytest

Tests use fully synthetic, API-shaped fixtures and make no network requests. Regenerate them with uv run python scripts/generate_fixtures.py.

See CONTRIBUTING.md for development guidelines.

License

MIT — see LICENSE.

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured