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Oura Ring
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python
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5 months ago
First Indexed
2 months ago
Catalog Refreshed
Documentation & install
Readme and setup notes from the catalogue, plus a client-ready config you can copy for your MCP host.
Installation
Add the following to your MCP client configuration file.
Configuration
View docs{
"mcpServers": {
"abekek-oura-mcp-python": {
"command": "python",
"args": [
"server.py"
],
"env": {
"OURA_PERSONAL_ACCESS_TOKEN": "YOUR_TOKEN_HERE"
}
}
}
}You can run an MCP server that gives you structured access to your Oura Ring health data. It lets you query sleep, activity, readiness, and other metrics through a simple MCP interface, so AI assistants and other clients can retrieve your data securely and efficiently.
How to use
You use this MCP server by connecting an MCP client to the local or remote server and issuing data requests for the metrics you care about. Each available tool represents a data endpoint you can query, such as daily sleep, readiness, activity, VO2 max, and personal information. You can filter results by date ranges when supported by a tool, with sensible defaults applied if you omit dates.
How to install
Prerequisites you need to prepare before starting the server:
- Python 3.10 or higher
- An Oura Ring and account
- Oura Personal Access Token (get one at cloud.ouraring.com/personal-access-tokens)
Step by step installation and run flow:
- Clone the project to your machine:
-
- git clone https://github.com/yourusername/oura-mcp-python.git
- cd oura-mcp-python
-
Install dependencies from the requirements file:
pip install -r requirements.txt
Create a configuration file with your Oura credentials, using the example as a starting point, then edit to include your token:
cp .env.example .env
# Edit .env and add your OURA_PERSONAL_ACCESS_TOKEN
Start the MCP server:
python server.py
Additional sections
Claude Desktop and Bedrock deployments are supported to run the MCP server in different environments. Use the recommended configuration to connect your client to the server.
Testing
You can verify your setup by running the test suite or test script before integrating with clients.
Configuration for Claude Desktop
Add the MCP server connection to Claude Desktop to enable direct querying from Claude.
AWS Bedrock Deployment
Deploy the MCP server to AWS Bedrock AgentCore using the provided deployment script or manual steps.
Usage examples
After configuration, you can ask for data such as sleep data for a date range, readiness scores, steps, workouts, VO2 max, and more. Use natural language prompts aligned with the available tools to retrieve the exact data you need.
Available tools
get_daily_sleep
Fetch daily sleep metrics including score, duration, efficiency, and sleep stages.
get_sleep_sessions
Retrieve detailed sleep sessions with heart rate, HRV, and movement data.
get_sleep_time
Return sleep timing information such as bedtime and wake time.
get_daily_readiness
Get daily readiness scores and contributing factors.
get_daily_activity
Query daily activity including steps, calories, and activity levels.
get_workouts
Fetch workout sessions with type, duration, and intensity.
get_sessions
Retrieve sessions like meditation and breathing exercises.
get_daily_spo2
Obtain daily blood oxygen saturation levels.
get_daily_stress
Access daily stress levels and recovery status.
get_daily_resilience
Get daily resilience scores and trends.
get_daily_cardiovascular_age
Estimate cardiovascular age from metrics.
get_vo2_max
Retrieve VO2 max measurements and trends.
get_ring_configuration
Query ring hardware configuration.
get_rest_mode_period
Fetch rest mode periods.
get_personal_info
Retrieve user profile information.