Intervals.icu MCP Server

Model Context Protocol (MCP) server for connecting Claude and ChatGPT with the Intervals.icu API. It provides tools for authentication and data retrieval for activities, events, and wellness data.

If you find the Model Context Protocol (MCP) server useful, please consider supporting its continued development with a donation.

Requirements

• Python 3.12 or higher
• Model Context Protocol (MCP) Python SDK
• httpx
• python-dotenv

Setup

1. Install uv (recommended)

curl -LsSf https://astral.sh/uv/install.sh | sh

2. Clone this repository

git clone https://github.com/mvilanova/intervals-mcp-server.git
cd intervals-mcp-server

3. Create and activate a virtual environment

# Create virtual environment with Python 3.12
uv venv --python 3.12

# Activate virtual environment
# On macOS/Linux:
source .venv/bin/activate
# On Windows:
.venv\Scripts\activate

4. Sync project dependencies

uv sync

5. Set up environment variables

Make a copy of .env.example and name it .env by running the following command:

cp .env.example .env

Then edit the .env file and set your Intervals.icu athlete id and API key:

API_KEY=your_intervals_api_key_here
ATHLETE_ID=your_athlete_id_here

Getting your Intervals.icu API Key

1. Log in to your Intervals.icu account
2. Go to Settings > API
3. Generate a new API key

Finding your Athlete ID

Your athlete ID is typically visible in the URL when you're logged into Intervals.icu. It looks like:

• https://intervals.icu/athlete/i12345/... where i12345 is your athlete ID

Updating

This project is actively developed, with new features and fixes added regularly. To stay up to date, follow these steps:

1. Pull the latest changes from main

⚠️ Make sure you don’t have uncommitted changes before running this command.

git checkout main && git pull

2. Update Python dependencies

Activate your virtual environment and sync dependencies:

source .venv/bin/activate
uv sync

Troubleshooting

If Claude Desktop fails due to configuration changes, follow these steps:

1. Delete the existing entry in claude_desktop_config.json.
2. Reconfigure Claude Desktop from the intervals_mcp_server directory:

mcp install src/intervals_mcp_server/server.py --name "Intervals.icu" --with-editable . --env-file .env

Usage with Claude

1. Configure Claude Desktop

To use this server with Claude Desktop, you need to add it to your Claude Desktop configuration.

1. Run the following from the intervals_mcp_server directory to configure Claude Desktop:

mcp install src/intervals_mcp_server/server.py --name "Intervals.icu" --with-editable . --env-file .env

2. If you open your Claude Desktop App configuration file claude_desktop_config.json, it should look like this:

{
  "mcpServers": {
    "Intervals.icu": {
      "command": "/Users/<USERNAME>/.cargo/bin/uv",
      "args": [
        "run",
        "--with",
        "mcp[cli]",
        "--with-editable",
        "/path/to/intervals-mcp-server",
        "mcp",
        "run",
        "/path/to/intervals-mcp-server/src/intervals_mcp_server/server.py"
      ],
      "env": {
        "INTERVALS_API_BASE_URL": "https://intervals.icu/api/v1",
        "ATHLETE_ID": "<YOUR_ATHLETE_ID>",
        "API_KEY": "<YOUR_API_KEY>",
        "LOG_LEVEL": "INFO"
      }
    }
  }
}

Where /path/to/ is the path to the intervals-mcp-server code folder in your system.

If you observe the following error messages when you open Claude Desktop, include the full path to uv in the command key in the claude_desktop_config.json configuration file. You can get the full path by running which uv in the terminal.

2025-04-28T10:21:11.462Z [info] [Intervals.icu MCP Server] Initializing server...
2025-04-28T10:21:11.477Z [error] [Intervals.icu MCP Server] spawn uv ENOENT
2025-04-28T10:21:11.477Z [error] [Intervals.icu MCP Server] spawn uv ENOENT
2025-04-28T10:21:11.481Z [info] [Intervals.icu MCP Server] Server transport closed
2025-04-28T10:21:11.481Z [info] [Intervals.icu MCP Server] Client transport closed

3. Restart Claude Desktop.

2. Use the MCP server with Claude

Once the server is running and Claude Desktop is configured, you can use the following tools to ask questions about your past and future activities, events, and wellness data.

• get_activities: Retrieve a list of activities
• get_activity_details: Get detailed information for a specific activity
• get_activity_intervals: Get detailed interval data for a specific activity
• get_wellness_data: Fetch wellness data
• get_events: Retrieve upcoming events (workouts, races, etc.)
• get_event_by_id: Get detailed information for a specific event

Usage with ChatGPT

ChatGPT’s beta MCP connectors can also talk to this server over the SSE transport.

1. Start the server in SSE mode so it exposes the /sse and /messages/ endpoints:

   export FASTMCP_HOST=127.0.0.1 FASTMCP_PORT=8765 MCP_TRANSPORT=sse FASTMCP_LOG_LEVEL=INFO
   python src/intervals_mcp_server/server.py
   

   The startup log prints the full URLs (for example http://127.0.0.1:8765/sse). ChatGPT needs that public URL, so forward the port with a tool such as ngrok http 8765 if you are not exposing the server directly.

2. In ChatGPT, open Settings → Features → Custom MCP Connectors and click Add. Fill in:

   • Name: Intervals.icu
   • MCP Server URL: https://<your-public-host>/sse
   • Authentication: leave as No authentication unless you have protected your tunnel.

   You can reuse the same ngrok http 8765 tunnel URL here; just ensure it forwards to the host/port you exported above.

3. Save the connector and open a new chat. ChatGPT will keep the SSE connection open and POST follow-up requests to the /messages/ endpoint announced by the server. If you restart the MCP server or tunnel, rerun the SSE command and update the connector URL if it changes.

Development and testing

Install development dependencies and run the test suite with:

uv sync --all-extras
pytest -v tests

Running the server locally

To start the server manually (useful when developing or testing), run:

mcp run src/intervals_mcp_server/server.py

Enabling debug logging

To capture server logs for debugging, wrap the command in a bash shell and redirect stderr to a file. Modify your claude_desktop_config.json like this:

{
  "mcpServers": {
    "Intervals.icu": {
      "command": "/bin/bash",
      "args": [
        "-c",
        "/Users/<USERNAME>/.local/bin/uv run --with 'mcp[cli]' --with-editable /path/to/intervals-mcp-server mcp run /path/to/intervals-mcp-server/src/intervals_mcp_server/server.py 2>> /path/to/intervals-mcp-server/mcp-server.log"
      ],
      "env": {
        "INTERVALS_API_BASE_URL": "https://intervals.icu/api/v1",
        "ATHLETE_ID": "<YOUR_ATHLETE_ID>",
        "API_KEY": "<YOUR_API_KEY>",
        "LOG_LEVEL": "INFO"
      }
    }
  }
}

Then tail the log file to see output in real-time:

tail -f /path/to/intervals-mcp-server/mcp-server.log

License

The GNU General Public License v3.0

Featured

Glama.ai