How do I get an Oura Personal Access Token?

Log in to your Oura account at [**cloud.ouraring.com**](https://cloud.ouraring.com/oauth2/authorize), create a personal access token in your account settings. The token gives access to your sleep, activity, readiness and health data.

What health data is available?

Sleep (score, stages, efficiency), Activity (steps, calories, MET), Readiness (score, HRV, RHR, temperature), Tags (mood, energy, behaviors), Workouts (type, duration, HR zones) and Heart Rate (5-min samples).

How far back can I access data?

You can access all historical data recorded by your Oura Ring. Use start_date and end_date parameters to filter results. Data is paginated with a nextToken for large date ranges.

Oura MCP Server for Pydantic AI 7 tools — connect in under 2 minutes

Name: Oura
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 7 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Oura through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to Oura "
            "(7 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Oura?"
    )
    print(result.data)

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Oura MCP Server

Connect your Oura Ring to any AI agent and access your personal health data through natural conversation.

Pydantic AI validates every Oura tool response against typed schemas, catching data inconsistencies at build time. Connect 7 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

Sleep — Analyze sleep scores, stages (REM/light/deep/wake), efficiency, latency and timing
Activity — Track daily steps, calories, MET minutes and activity goals
Readiness — Monitor readiness scores, HRV, resting heart rate, body temperature and recovery
Tags — Review your manual entries for mood, energy, behaviors and substances
Workouts — Browse logged workouts with type, duration, calories and heart rate zones
Heart Rate — Access detailed 5-minute heart rate samples and HRV data

The Oura MCP Server exposes 7 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Oura to Pydantic AI via MCP

Follow these steps to integrate the Oura MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 7 tools from Oura with type-safe schemas

Why Use Pydantic AI with the Oura MCP Server

Pydantic AI provides unique advantages when paired with Oura through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Oura integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your Oura connection logic from agent behavior for testable, maintainable code

Oura + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Oura MCP Server delivers measurable value.

Type-safe data pipelines: query Oura with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Oura tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Oura and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Oura responses and write comprehensive agent tests

Oura MCP Tools for Pydantic AI (7)

These 7 tools become available when you connect Oura to Pydantic AI via MCP:

get_activity

Supports date range filtering. Get your Oura activity data

get_heart_rate

Returns timestamp, heart rate value and HRV for each sample. Supports date range filtering. Note: This endpoint returns high-frequency data; use narrow date ranges. Get your Oura heart rate data

get_readiness

Supports date range filtering. Get your Oura readiness data

get_sessions

Includes overall scores, sleep metrics, activity data and readiness indicators. Supports date range filtering. Get your Oura session data

get_sleep

Supports date range filtering with start_date and end_date (YYYY-MM-DD). Pagination via nextToken. Get your Oura sleep data

get_tags

). Tags are user-entered data points that correlate with sleep and readiness scores. Supports date range filtering. Get your Oura tags

get_workouts

Workouts can be manually logged or auto-detected by the Oura Ring. Supports date range filtering. Get your Oura workout data

Example Prompts for Oura in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Oura immediately.

"How did I sleep last night?"

"What is my readiness score today?"

"Show me my activity from yesterday."

Troubleshooting Oura MCP Server with Pydantic AI

Common issues when connecting Oura to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Oura + Pydantic AI FAQ

Common questions about integrating Oura MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your Oura MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.