Oura MCP server

Oura MCP server

A Model Context Protocol (MCP) server that gives Claude read-only access to yourOura ring biometrics via the Oura API v2.

It's designed to sit alongside a Strava connector: every tool is namespaced oura_* andkeyed by ISO date (YYYY-MM-DD), so Claude can join Oura recovery data against Strava trainingload on date and answer questions like "how did last week's hard sessions affect my sleep,stress, and next-day readiness?" in one reasoning step.

_{Illustrative example using sample data, not real biometrics.}

Tools

All output is compact CSV with units stated in the column names.

Setup

python -m venv .venv && source .venv/bin/activate   # Windows: .venv\Scripts\activate
pip install -e .

New here? The full setup & configuration guide walks through install,token creation, the Claude Desktop config, common mistakes, and troubleshooting.

Authentication

This server uses an Oura Personal Access Token (PAT):

1. Go to https://cloud.ouraring.com/personal-access-tokens and create a token.
2. Copy .env.example to .env and paste the token into OURA_PERSONAL_ACCESS_TOKEN(for local dev), or set it in the Claude Desktop env block below.

Never commit your real token — .env is gitignored.

Run / test

fastmcp dev server.py     # opens the MCP Inspector to exercise each tool manually

Install in Claude Desktop

Edit claude_desktop_config.json (macOS: ~/Library/Application Support/Claude/,Windows: %APPDATA%\Claude\) and add:

{
  "mcpServers": {
    "oura": {
      "command": "/Users/ericcarr/Documents/GitHub/oura-mcp-server/.venv/bin/python",
      "args": ["/Users/ericcarr/Documents/GitHub/oura-mcp-server/server.py"],
      "env": {
        "OURA_PERSONAL_ACCESS_TOKEN": "your-token-here"
      }
    }
  }
}

Use the venv's Python interpreter and an absolute path to server.py. Fully quit and reopenClaude Desktop after editing. The oura_* tools then appear in the tools/connectors menu,ready to use alongside your Strava tools.

Usage & examples

Once the server is connected, just ask Claude in plain language — it picks the right tool(s) anddate ranges. A few patterns that work well:

Oura on its own

• "Pull my Oura daily summary for the last two weeks."
• "Did my readiness drop after any night this month? Show me why." → oura_get_readiness_detail
• "Break down last night's sleep stages and compare them to my 14-day average." → oura_get_sleep_detail
• "Which days this month were most stressful, and how's my resilience trending?" → oura_get_stress_resilience
• "How's my VO2 max and SpO2 trending over the last 90 days?" → oura_get_baselines
• "What was my heart rate during yesterday's workout vs. overnight?" → oura_get_heart_rate

The headline use case — Oura + Strava together

Because both connectors are date-keyed, Claude can join them on date in one step:

• "Compare last month's Strava training load against my Oura readiness and sleep. Flag any daysI overreached (readiness or HRV dropped the morning after a hard session)."
• "After my long runs, how much does my resting heart rate rise the next morning, and how longuntil it recovers to baseline?"
• "Do my hardest training days hurt that night's deep sleep? Show the correlation."
• "Reconcile my Strava activities with Oura's logged workouts for the past month — did Oura catchanything Strava missed?" → oura_get_workouts
• "Build me a weekly table: Strava distance & suffer score next to Oura sleep score, avg HRV, andnext-day readiness, so I can see if my training plan is sustainable."

What the data looks like

Tools return compact CSV with units in the column names — easy for Claude to reason over and join.For example, oura_get_daily_summary returns rows like:

date,readiness_score,sleep_score,activity_score,total_sleep_h,resting_hr_bpm,avg_hrv_ms,temp_deviation_c,steps,active_cal,stress_high_min,day_summary
2026-06-05,78,84,95,8.31,52,79,-0.16,8122,1211,360,stressful
2026-06-06,63,60,97,5.14,74,12,-0.19,7667,941,240,stressful
2026-06-07,85,87,96,7.95,60,37,0.13,7768,919,30,normal

Here the high-load, high-stress day (Jun 5: 1,211 active cal, 360 stressful min) is followed by areadiness crash (84→63), a resting-HR spike (52→74 bpm), and an HRV collapse (79→12 ms) — exactlythe training-to-recovery signal this server is built to surface.

Tip: start broad with oura_get_daily_summary, then drill into a specific day or signal withthe detail tools (oura_get_readiness_detail, oura_get_sleep_detail). Keep date ranges modestto stay fast and within Oura's rate limit.

Notes & limits

• Read-only. No tool writes to your Oura account.
• Dates are ISO YYYY-MM-DD and the range is inclusive. Heart rate uses ISO 8601 datetimes.
• Some metrics are sparse or ring/firmware-dependent (VO2 max, cardiovascular age, resilienceneed enough history); rows show blanks where a metric wasn't measured.
• Oura's rate limit is ~5000 requests/day; tools default to modest windows and paginateautomatically.