The full upstream README, mirrored here for reference. Install config, tool schemas, adoption signals, and an original overview live on the Oura Ring listing page.
An MCP server that gives Claude (or any MCP client) read-only access to your Oura Ring
data: sleep, readiness, activity, stress, SpO2, resilience, workouts, sessions and heart
rate. It talks to the Oura API v2 with its own small
async client (oura_ring_mcp.core).
| Tool | Returns |
|---|---|
get_personal_info | Age, weight, height, biological sex, email |
get_daily_sleep | Daily sleep score and contributors |
get_sleep_periods | Each night's sleep and naps: stages, efficiency, heart rate, HRV |
get_daily_readiness | Daily readiness score, contributors, temperature deviation |
get_daily_activity | Daily activity score, steps, calories, time per activity level |
get_daily_stress | Daily time in high stress and in recovery |
get_daily_spo2 | Nightly average SpO2 and breathing disturbance index |
get_daily_resilience | Daily resilience level and contributors |
get_workouts | Workouts with type, intensity, calories, distance |
get_sessions | Meditation, breathing and rest sessions |
get_heart_rate | Heart rate samples with min, max and average bpm |
Daily tools take optional start_date and end_date (YYYY-MM-DD, both inclusive).
Without them they cover the 7 days ending today; ranges are limited to 90 days. Each
result echoes the range it covers, so the model always knows what "today" meant.
get_heart_rate takes optional start_datetime and end_datetime (ISO 8601). Without
them it covers the last 24 hours; windows are limited to 7 days.
Per-interval series (5-minute activity classes, MET, sleep phases, in-sleep heart rate and HRV curves) are left out of results to keep them small; the scores, totals and averages are kept.
For a step-by-step guide, including creating the Oura application and troubleshooting, see the installation guide. Full documentation is at https://oura-ring-python-mcp.readthedocs.io.
The server signs in with OAuth2, since Oura has deprecated personal access tokens. You
need an Oura API application (a client ID and secret) whose redirect URIs include
http://localhost:47651/callback, with the scopes email, personal, daily,
heartrate, workout, session, spo2 and stress allowed (resilience needs
stress). Gen3 and Oura Ring 4 users need an active Oura
membership for the API to return data.
Sign in once. This opens the browser, catches Oura's redirect on localhost, and saves
the tokens to ~/.config/oura-ring-mcp/tokens.json (readable only by you):
From then on the server refreshes the access token by itself (Oura issues them for 30 days)
and saves each new single-use refresh token. Run auth again only if you revoke access
or the saved refresh token is lost.
| Variable | Required | Default | Meaning |
|---|---|---|---|
OURA_CLIENT_ID | yes | Client ID of your Oura API application | |
OURA_CLIENT_SECRET | yes | Client secret of your Oura API application | |
OURA_TOKEN_FILE | no | ~/.config/oura-ring-mcp/tokens.json (under $XDG_CONFIG_HOME if set) | Where auth saves the tokens and the server reads them |
OURA_TIMEZONE | no | the machine's time zone | Your IANA time zone, e.g. Europe/London, so "today" matches Oura's days. Set it when running in Docker, where the default is UTC |
OURA_REDIRECT_URI | no | http://localhost:47651/callback | Must match a redirect URI of the application exactly |
OURA_SCOPES | no | email personal daily heartrate workout session spo2 stress | Scopes to request |
If the redirect URI isn't http://localhost:<port>/... (or you're signing in over SSH
or in Docker), auth asks you to paste the URL the browser ended up on instead; force
that with auth --paste.
No clone needed; uv fetches and runs the published package:
In a client config, use "command": "uvx", "args": ["oura-ring-python-mcp"].
Sign in on the host first (above), then mount the token folder so the container can
read the tokens and save refreshed ones. The server speaks MCP over stdio, so keep -i:
The image reads the tokens from /tokens/tokens.json. --user lets the container read
and update your token file on Linux; Docker Desktop on macOS and Windows doesn't need it.
To sign in from the container instead, run it with -it and the command auth --paste.
In a client config, use "command": "docker" with those arguments, and pass the
variables through the client's env block.
Add to claude_desktop_config.json:
Each tool call becomes a Langfuse trace, with a child span for each Oura API call. Install the extra and set the keys:
In the server command, use run --extra langfuse oura-ring-python-mcp instead of
run oura-ring-python-mcp.
| Variable | Meaning |
|---|---|
LANGFUSE_PUBLIC_KEY, LANGFUSE_SECRET_KEY | Tracing is on only when both are set |
LANGFUSE_BASE_URL | Langfuse URL for self-hosted or regional instances (default: Langfuse Cloud) |
LANGFUSE_CAPTURE_DATA | true to include tool inputs, outputs and error messages. Default false |
Privacy: sleep, heart rate and activity data are health data. By default, traces hold
only tool names, timings and error class names. Setting LANGFUSE_CAPTURE_DATA=true
sends your data to your Langfuse instance; only do that with an instance you trust, such
as a self-hosted one.
Bump version in pyproject.toml and both versions in server.json (a test checks they
match), commit, then push a tag:
The tag publishes to PyPI (pypi.yml, needs the PYPI_API_TOKEN secret), to
ghcr.io/osjayaprakash/oura-ring-python-mcp (docker.yml), and then to the
MCP Registry (mcp-registry.yml).