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google-health-mcp

health_get_heart_rate

Retrieve daily resting heart rate and heart rate zone breakdown for a date range from Google Health, using local cached data or a live refresh.

Instructions

Get daily resting heart rate and heart rate zones.

Returns resting HR and zone breakdown (Out of Range, Fat Burn, Cardio, Peak) from the local cache by default, auto-syncing if stale.

Args: start_date: Start date as "YYYY-MM-DD", "YYYY-MM", or "30d". Default: last 30 days. end_date: End date as "YYYY-MM-DD". Default: today. live: If true, re-fetch this window from the API before reading the cache.

Returns one entry per day with resting_hr, zones array, calculation_method (Google's WITH_SLEEP or ONLY_WITH_AWAKE_DATA) and data_source (the device and platform Google says recorded it). Zone data: name, minutes, caloriesOut, max/min HR for each zone. Zones are present only on days that arrived by import; a sync does not write them.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
liveNo
end_dateNo
start_dateNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.5/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden and does so well: it discloses cache-first behavior, automatic staleness sync, the effect of 'live', and the important quirk that zone data only exists on days that arrived via import and is not written by a sync. It does not mention auth/permission requirements or rate limits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loads purpose, then behavior, then args, then return shape. Slightly verbose in the returns section, but every sentence (zones-only-on-import, calculation_method) adds real information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so the description did not need the return-value detail it provided, yet that detail (resting_hr, zones, calculation_method, data_source) is accurate and helpful. Combined with cache/sync semantics, nothing an agent needs to call this correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate, and it does: it gives accepted date formats ('YYYY-MM-DD', 'YYYY-MM', '30d') and defaults for start_date, a format and default for end_date, and the operational meaning of live. All three parameters are fully specified.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Get daily resting heart rate and heart rate zones') and the exact payload. It is clearly distinguishable from sibling tools like health_get_hrv, health_get_spo2, and health_get_sleep_sessions.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explains the default operating mode (local cache, auto-sync if stale) and gives a clear condition for using 'live' (re-fetch this window from the API). No explicit sibling routing or when-not-to-use guidance, but the context an agent needs to choose parameter values is present.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.