Aidlab MCP
OfficialClick on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Aidlab MCPSummarize my sleep and activity for the last seven days."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Aidlab MCP
Connect your Aidlab wellness data to AI tools through the Model Context Protocol.
Public preview: no invite or allowlist is required. The server is read-only and every request is limited to the Aidlab user who approved the connection.
Endpoint
https://my.aidlab.com/mcpTransport: stateless Streamable HTTP. Stable MCP protocol: 2025-11-25.
Related MCP server: WHOOP MCP Server
Available tools
Tool | Result |
| Daily steps, average heart rate, average HRV, sleep, and activity duration |
| Step measurements |
| Heart rate measurements in BPM |
| HRV measurements in milliseconds |
| Sleep-stage intervals |
| Recorded workout intervals |
| Language and timezone only |
All tools are read-only and idempotent. Health-data tools require data:read; profile requires profile:read.
Connect
Add this remote MCP URL in your AI client:
https://my.aidlab.com/mcpThe client discovers Aidlab OAuth, identifies itself with a Client ID Metadata Document (CIMD) or registers a public client dynamically (DCR), opens Aidlab sign-in and consent, and stores the resulting credentials. No API key, manually created OAuth client, pasted token, invite, or allowlist is required.
Codex CLI
codex mcp add aidlab --url https://my.aidlab.com/mcpCodex starts Aidlab OAuth automatically. If authentication was skipped or revoked, run codex mcp login aidlab --scopes data:read,profile:read. Open /mcp to verify the connection. See examples/codex-config.toml for the equivalent configuration.
ChatGPT desktop and web
Create a custom MCP connection and enter https://my.aidlab.com/mcp. ChatGPT follows the same Aidlab login and consent flow.
Claude and Claude Code
Add the remote URL as a custom connector. For a project configuration, copy examples/claude-code.mcp.json; authentication is completed interactively.
OpenAI Responses API
The server-side example in examples/openai-responses.mjs is for advanced integrations that already manage OAuth credentials. It requires approval before every health-data tool call; secrets belong in server-side configuration, never browser code.
Try it
npm run smokeThe public smoke verifies OAuth discovery and the unauthenticated challenge without credentials. Maintainers may additionally set a short-lived OAuth AIDLAB_TOKEN to verify the authenticated MCP lifecycle and exact tool surface.
Then ask:
“Summarize my sleep and activity for the last seven days. Mention missing data.”
“Compare my daily steps and average heart rate this week with the previous week.”
“List yesterday's workouts and sleep stages. Do not give medical advice.”
Each date-range call accepts at most 31 days. Raw-list tools return at most 200 records per page; use the returned next cursor as the next end_date when has_more is true.
See docs/tools.md for inputs, outputs, units, and missing-data behavior.
Privacy and safety
Tool inputs do not contain
owner_id,user_id, or a general-purpose query field./mcpaccepts only one-hour OAuth access tokens bound to the MCP resource; the approving user and scopes are enforced by Aidlab's authorization layer.Outputs omit identity, contact details, source metadata, billing fields, and raw physiological signals.
The AI client or API provider you choose receives the requested wellness results and a resource-bound access token so it can call Aidlab; review that provider's data controls before use.
Results are wellness data, not medical diagnosis or treatment advice.
See SECURITY.md for vulnerability reporting, plus Aidlab's Privacy Policy and Terms.
License
The configuration examples and smoke client in this repository are MIT licensed. The hosted Aidlab service and its backend remain proprietary and are governed by Aidlab's terms.
This server cannot be deployed
Maintenance
Related MCP Connectors
Connect your health, fitness, nutrition, sleep, and wearable data to your AI assistant.
- freddyOAuthcoach.freddy
Connect your wearables, rings and training apps, then ask your AI about your own health data.
Zero-setup MCP gateway securely connecting AI to your tools with authentication and workflows
Pace is a remote MCP server that exposes wearable and fitness data to Claude via the Model Context Protocol. It connects to Garmin, Oura, Whoop, Polar, Fitbit and 20+ devices and provides 15 tools for querying sleep, activity, recovery, and training data. Hosted on Google Cloud Run, OAuth 2.1 authentication, Streamable HTTP transport. Instructions: First you need to create an account at: https://pacetraining.co and connect your wearables. After that you can connect the remote Server via Custom Connector in Claude and OAuth 2.1 Flow startet.
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