Oura Ring MCP Server

Oura Ring MCP Server

Enables Claude to access and query Oura Ring health data including sleep, activity, readiness, heart rate, and more via the Oura API.

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Oura Ring MCP Server

An MCP (Model Context Protocol) server that provides Claude with access to the Oura Ring health data API. Access your sleep, activity, readiness, heart rate, and other health metrics through Claude.

Features

  • Sleep data — daily scores, detailed periods, HRV, sleep phases
  • Activity data — steps, calories, active time, scores
  • Readiness data — readiness scores, body temperature, contributors
  • Heart rate — continuous HR samples with source context
  • Stress & resilience — stress levels, recovery time, resilience
  • SpO2 — blood oxygen saturation data
  • Workouts & sessions — exercise tracking, meditation sessions
  • Sleep recommendations — optimal bedtime window

Setup

1. Get Oura API Credentials

  1. Go to Oura Developer Portal
  2. Create a new application
  3. Note your Client ID and Client Secret

2. Install

# Clone the repository
git clone <repo-url>
cd oura-mcp-server

# Install in development mode
pip install -e ".[dev]"

3. Configure

# Copy the example environment file
cp .env.example .env

# Edit with your credentials
# OURA_CLIENT_ID=your_client_id
# OURA_CLIENT_SECRET=your_client_secret

4. Run

# Run with stdio transport (for local MCP clients)
oura-mcp

# Or run directly
python -m oura_mcp.server

Authentication

The server uses OAuth2 Authorization Code flow. On first use:

  1. Call start_authentication to get an authorization URL
  2. Visit the URL and authorize the application
  3. Copy the authorization code
  4. Call complete_authentication with the code

Tokens are stored locally at ~/.config/oura-mcp/tokens.json and automatically refresh when expired.

Available Tools

Data Tools

Tool Description
get_sleep_summary Daily sleep scores and contributors
get_sleep_details Detailed sleep periods (HRV, phases, HR)
get_sleep_recommendations Optimal bedtime window
get_activity_summary Steps, calories, active time, score
get_readiness_summary Readiness score and contributors
get_stress_data Stress/recovery time, day summary
get_spo2_data Blood oxygen levels
get_heart_rate HR samples with source context
get_workouts Activity type, duration, calories
get_sessions Meditation/rest/breathing sessions
get_personal_info User profile
get_daily_resilience Resilience level and contributors

Auth Tools

Tool Description
check_auth_status Check if account is connected
start_authentication Start OAuth2 flow
complete_authentication Complete OAuth2 flow with code
disconnect_account Remove stored credentials

Cloud Deployment (Railway)

For deploying as a remote MCP server:

# Set environment variables on Railway
OURA_CLIENT_ID=your_client_id
OURA_CLIENT_SECRET=your_client_secret
OURA_ACCESS_TOKEN=your_access_token
OURA_REFRESH_TOKEN=your_refresh_token

The server uses SSE transport when deployed to cloud. See cloud_server.py and Dockerfile.

Claude.ai Integration

Add to your Claude.ai MCP server configuration:

{
  "mcpServers": {
    "oura": {
      "url": "https://your-deployment-url.railway.app/sse"
    }
  }
}

Development

# Run tests
pytest

# Lint
ruff check .

# Format
ruff format .

License

MIT

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