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Glama
kirollosatef

google-health-mcp

by kirollosatef

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
GOOGLE_CLIENT_IDYesYour Google Cloud OAuth client ID
GOOGLE_CLIENT_SECRETYesYour Google Cloud OAuth client secret
HEALTH_BASELINE_DAYSNoNumber of days used for baseline calculations. Default is 30.30

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Features and capabilities supported by this server

Protocol revision2025-11-25

CapabilityDetails
tools
{
  "listChanged": false
}
prompts
{
  "listChanged": false
}
resources
{
  "subscribe": false,
  "listChanged": false
}
experimental
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
health_auth_statusA

Check whether the server holds valid Google Health credentials.

Call this first if any other tool returns a not_authorized error.

health_data_typesA

List every readable data type, with the ones a Fitbit Air produces flagged.

health_profileA

Google Health profile, unit/timezone settings, and paired devices with sync state.

health_pointsA

Read raw data points for one data type over a date range (YYYY-MM-DD, inclusive).

reconcile=True returns Google's merged cross-source stream (tracker + phone + manual entries deduplicated), which is almost always what you want.

This is the low-level escape hatch. For daily questions prefer health_daily or health_daily_brief - a single day of heart-rate can be 1440 points.

health_dailyA

Daily aggregate for one data type over a date range (YYYY-MM-DD, inclusive).

Uses civil-day rollups, so days align to your local calendar rather than UTC.

health_daily_briefA

One-call snapshot of a single day: sleep, resting HR, HRV, SpO2, breathing rate, skin temperature, steps and active zone minutes, each compared against your own trailing baseline.

This is the right first call for "how am I doing today". Defaults to today.

health_trendA

Week-over-week trend for one metric: weekly means, direction, and the change from the first week to the most recent.

Use this to answer "is my sleep actually getting worse" rather than reacting to a single bad night.

health_readinessA

Recovery readiness for a day: HRV, resting HR, breathing rate and SpO2 each scored against your personal baseline, plus rolling sleep debt, combined into a train / hold / rest call with the reasoning shown.

Returns confidence and missing_inputs so you can tell a real signal from thin data. Informational only, not a medical assessment.

health_anomaliesA

Scan recent days for metrics that moved more than threshold standard deviations from your own trailing baseline.

Surfaces the handful of days worth talking about instead of a wall of numbers.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

TDQS

A4.1/5.0

Scored across 9 tools

Disambiguation5/5

Each tool has a clearly distinct purpose: auth check, data type listing, profile, daily multi-metric brief, weekly trend, readiness, anomaly scan, raw points, and daily aggregate. No overlap between tools; health_daily_brief and health_daily differ by scope (single day vs range) and metric count.

Naming Consistency5/5

All tools follow a consistent health_ prefix with descriptive snake_case suffixes (auth_status, data_types, profile, daily_brief, trend, readiness, anomalies, points, daily). The pattern is uniform and predictable.

Tool Count5/5

9 tools is a well-scoped number for a health data server. Each tool covers a distinct aspect of reading and analyzing health metrics without redundancy or bloat.

Completeness4/5

The tool surface covers authentication, data discovery, profile, daily snapshots, trends, readiness, anomalies, raw data, and daily aggregates. Minor gap: no direct way to get multiple metrics across a date range in one call, but this can be composed from existing tools.

Maintenance

ActivityMaintained
ResponsivenessNo issues