Skip to main content
Glama
Google Health MCP

Google Health MCP

by Kian-hdr

get_body_metrics

Read-onlyIdempotent

Summarize recent weight, body-fat, temperature, height, and blood-glucose records with normalized units and source metadata, filtering by time range, source, and duplicate resolution.

Instructions

Summarize recent weight, body-fat, temperature, height, and blood-glucose records with normalized units and source metadata.

Input Schema

NameRequiredDescriptionDefault
daysNo
sourceNoSource filter: FITBIT, HEALTH_KIT, or allall
timezoneNoUTC
deduplicateNoRemove exact duplicates and resolve same-time cross-source conflicts using source_priority
source_priorityNoPriority used when sources conflict

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.1

TDQS

B3.3/5.0
Behavior3/5

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

Annotations already declare readOnly, idempotent, non-destructive, open-world, so the safety profile is covered. The description adds useful behavioral context by noting normalized units and source metadata in the output, but says nothing about how the 90-day cap or cross-source conflict resolution affects results beyond what the schema already states.

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

Conciseness5/5

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

A single front-loaded sentence that lists scope and output qualities with no filler. Every clause carries information.

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

Completeness3/5

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

For a read-only aggregate tool with strong annotations and no output schema, the description covers what is returned at a high level (normalized units, source metadata), which is helpful. It is still thin on the default/limit behavior of the time window and on source-conflict handling, which are the parameters most likely to change results.

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

Parameters3/5

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

Schema coverage is 60%: source, deduplicate, and source_priority are documented in the schema, while 'days' and 'timezone' are undocumented. The description only implies the recency window and adds no format or semantics detail for source selection, timezone handling, or deduplication.

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

Purpose4/5

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

The description names a specific verb ('Summarize') and enumerates the exact resources covered (weight, body-fat, temperature, height, blood-glucose), so the agent knows precisely what data comes back. It does not differentiate itself from close siblings like get_recent_metrics or get_metrics, which a reader would need to disambiguate.

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

Usage Guidelines2/5

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

There is no statement of when to choose this tool over get_metrics, get_recent_metrics, or get_health_snapshot. 'Recent' hints at a time-window use case but no window, exclusion, or alternative is specified.

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