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Oura MCP Server

Oura MCP Server exposes your Oura Ring API v2 data through Model Context Protocol (MCP), so AI assistants can query sleep, activity, stress, heart rate, workouts, readiness, and more. What You Get - 15+ MCP tools covering sleep, recovery, activity, vitals, and device/profile data.

Pricing

from $10.00 / 1,000 results

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MCP servers

Integrations

You can access the Oura MCP Server programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in Integrations settings in Apify Console.

Python

JavaScript

CLI

OpenAPI

HTTP

MCP

1from apify_client import ApifyClient
2
3# Initialize the ApifyClient with your Apify API token
4# Replace '<YOUR_API_TOKEN>' with your token.
5client = ApifyClient("<YOUR_API_TOKEN>")
6
7# Prepare the Actor input
8run_input = {}
9
10# Run the Actor and wait for it to finish
11run = client.actor("unlimiteddots/oura-mcp-server").call(run_input=run_input)
12
13# Fetch and print Actor results from the run's dataset (if there are any)
14print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
15for item in client.dataset(run["defaultDatasetId"]).iterate_items():
16    print(item)
17
18# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

Oura MCP Server API in Python

The Apify API client for Python is the official library that allows you to use Oura MCP Server API in Python, providing convenience functions and automatic retries on errors.

Install the apify-client

$pip install apify-client

Other API clients include:

Oura MCP Server API in JavaScript

Oura MCP Server API through CLI

Oura MCP Server OpenAPI definition

Oura MCP Server API

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