withings-mcp
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Related Servers
- AlicenseNot gradedqualityDmaintenanceAn MCP server that connects Claude to Withings health data using OAuth 2.0. Provides 11 read-only tools to access body measurements, activity, sleep, heart rate, and device information from Withings devices.MIT
- AlicenseNot gradedqualityCmaintenanceEnables reading Withings smart-scale data (weight, body composition, etc.) through MCP tools, with OAuth2 authentication and automatic token refresh.MIT
- AlicenseNot gradedqualityAmaintenanceA Model Context Protocol (MCP) server that brings your Withings health data into Claude, allowing natural conversation access to sleep patterns, body measurements, workouts, heart data, and more.42MIT
- AlicenseBqualityAmaintenanceLocal-first MCP server that connects AI agents to your Withings body, sleep, activity and heart data.23140 npm5MIT
- AlicenseAqualityCmaintenanceMCP server for the Withings Health API with per-user OAuth2, enabling users to securely access their own health data (measures, activity, sleep, workouts, heart rate, devices, and goals) and optionally add measurements.12Apache 2.0
- AlicenseNot gradedqualityBmaintenanceEnables Claude to access and query personal Oura Ring health data, including activity, readiness, sleep, workouts, heart rate, stress, SpO2, sessions, and tags, via a self-hosted MCP server.MIT
TDQS
Scored across 5 tools
Each tool maps to a clearly distinct data domain: connection status, devices, body measurements, activity, and sleep. There is no overlap in purpose, and the descriptions anchor each to a specific resource. An agent can select the right tool unambiguously.
All five tools follow the same predictable withings_<noun> pattern (status, devices, measurements, activity, sleep). No verb-style mixing or case inconsistencies. The naming is uniform and readable.
Five tools is well-scoped and each earns its place by covering a major Withings data category. It is slightly thin in that related surfaces (e.g. workouts, user profile) are not exposed, but nothing feels redundant or padded.
The set provides solid read coverage across status, devices, measurements, activity, and sleep, covering the core lifecycle of a health-data reader. Minor gaps remain, such as workouts or intraday data, but core agent workflows are supported without dead ends.