Google Health MCP
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- AlicenseNot gradedqualityCmaintenanceEnables MCP clients to access Oura Ring health data such as sleep, readiness, activity, workouts, HRV, and event-centered recovery timelines using OAuth2 authentication.MIT
- AlicenseBqualityBmaintenanceEnables MCP clients such as Claude to query Fitbit and Pixel Watch health data — sleep, steps, heart rate, HRV, workouts, weight and nutrition — through the Google Health API, with built-in OAuth 2.0 sign-in and multi-user access so it can be hosted remotely and reached from web, desktop and mobile.26MIT
- AlicenseAqualityCmaintenanceProvides local, read-only MCP access to Google Health API v4, enabling users to query recorded workouts, heart-rate samples, and related health data through natural language in an MCP client.337 npmMIT
- AlicenseNot gradedqualityDmaintenanceRead-only MCP access to Fitbit-synced health data through Google Health API v4. Provides tools for metrics, summaries, trends, and data quality without write or arbitrary HTTP operations.MIT
- AlicenseNot gradedqualityBmaintenanceA remote MCP server that gives MCP clients read-only, OAuth-authenticated access to Google Health API data such as activity, sleep, heart, body, nutrition and ECG records. It exposes tools for profiles, paired devices, data points, daily summaries and time-window rollups, and is deployed on Cloudflare Workers.37 npm1MIT
- AlicenseNot gradedqualityBmaintenanceSelf-hosted multi-user Google Health OAuth broker and read-only Agent API with remote MCP support. Enables users to connect their Google account and grant agents secure access to activity, sleep, heart, HRV, SpO2, and other health metrics via revocable per-token authentication.3MIT
TDQS
Scored across 17 tools
Several tools are hard to tell apart: get_health_snapshot, get_daily_summary, get_activity_summary, and get_recovery_summary all return overlapping subsets of the same daily Fitbit metrics, and get_metrics vs get_recent_metrics vs get_trends vs compare_periods all read numeric ranges with different wrappers. get_data_source_info, get_data_quality, and get_sync_status also sit close together (provenance vs coverage vs account state) even though descriptions attempt to differentiate them. The list/get primitives (profile, devices, settings, sleep) are clearly distinct.
Every tool follows a snake_case verb_noun pattern (get_*, list_*, compare_*), with no camelCase or stylistic drift. Names map predictably onto the returned resource, making the surface easy to scan.
17 tools is at the heavy end for a read-only metrics server, and much of that count comes from summary variants (snapshot, daily, activity, recovery, body) that largely recombine the same underlying metrics. The count is defensible given the breadth of health domains, but a few tools feel redundant rather than earning their place.
For an explicitly read-only integration, coverage is solid: discovery, raw metric reads, trends, period comparison, data-quality diagnostics, sleep, body, activity, recovery, plus account/device/profile/settings context. Gaps remain in nutrition/water intake, exercise/activity session logs, and intraday heart-rate resolution, which agents may need to work around.