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tomekkorbak/oura-mcp-server

by Various

MCP server for Oura API integration

T

MCP

tomekkorbak/oura-mcp-server

Added 1 June 2026

#mcp #oura-ring

Overview

A Model Context Protocol (MCP) server that provides an interface for connecting AI agents to the Oura API. It enables retrieval of health and sleep data from Oura ring users through standard MCP tool calls.

Best for

Best for
Developers building MCP-compatible AI agents that need access to Oura wearable data.

Use cases

  • Building AI assistants that can query personal Oura ring health metrics
  • Automating health data analysis workflows using Oura's API
  • Integrating Oura sleep and activity data into agentic applications

How to use

Tools exposed

  • get_sleep_data
  • get_readiness_data
  • get_resilience_data
  • get_today_sleep_data
  • get_today_readiness_data
  • get_today_resilience_data

Tested with

Claude for Desktop

Example client config

{\n    "mcpServers": {\n        "oura": {\n            "command": "uvx",\n            "args": [\n                "oura-mcp-server"\n            ],\n            "env": {\n                "OURA_API_TOKEN": "YOUR_OURA_API_TOKEN"\n            }\n        }\n    }\n}

Notes

A Model Context Protocol (MCP) server that provides an interface for connecting AI agents to the Oura API. It enables retrieval of health and sleep data from Oura ring users through standard MCP tool calls.

37 stars on GitHub. Last updated 2025-02-27. Licensed MIT.

Use cases

  • Building AI assistants that can query personal Oura ring health metrics
  • Automating health data analysis workflows using Oura’s API
  • Integrating Oura sleep and activity data into agentic applications

Pros

  • Open-source Python implementation, easy to extend or modify
  • Leverages the MCP standard for interoperability with AI agents
  • Small, focused codebase: 37 stars suggests early-stage but functional

Cons

  • Limited community and documentation due to low number of stars and contributions
  • Requires Oura API credentials and user authorization setup
  • May not cover all Oura API endpoints or handle rate limiting robustly yet

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Open-source Python implementation, easy to extend or modify
  • Leverages the MCP standard for interoperability with AI agents
  • Small, focused codebase: 37 stars suggests early-stage but functional

Cons

  • Limited community and documentation due to low number of stars and contributions
  • Requires Oura API credentials and user authorization setup
  • May not cover all Oura API endpoints or handle rate limiting robustly yet
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