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google-health-mcp

health_get_weight

Retrieve daily weight, BMI, and body fat percentage entries from a local cache or the Google Health API for trend tracking; sync first to populate offline data.

Instructions

Get weight log entries (weight, BMI, body fat percentage).

Returns data from the local cache by default. Use live=True to fetch from the API. Run health_sync first to populate the cache.

Weight data is sparse: only days with weigh-in entries are present.

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 weight_kg, bmi, fat_pct. Every individual weigh-in is in health_get_weight_readings.

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

A4.9/5.0
Behavior5/5

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 the caching model, that live=True re-fetches the window before reading, the sync prerequisite, and that the data is sparse (only weigh-in days present). These are exactly the behavioral traits an agent needs.

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 and cache semantics before the args, with zero filler sentences. Minor redundancy: the fields weight_kg, bmi, fat_pct are restated in the Returns block after already being named in the opening line.

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?

Although an output schema exists (so return-value documentation is optional), the description still completes the picture with cache/live behavior, sparse-data caveat, sync prerequisite, and full parameter formats. Nothing needed to call it 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 coverage is 0%, so the description must fully compensate, and it does: it documents all three params, including accepted start_date formats (YYYY-MM-DD, YYYY-MM, relative '30d') and defaults for start_date, end_date, and live that the schema does not express.

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+resource (get weight log entries) with the exact fields returned (weight, BMI, body fat percentage). It explicitly distinguishes itself from the sibling health_get_weight_readings by noting that individual weigh-ins live there while this tool returns one entry per day.

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

Usage Guidelines5/5

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

Explicitly states the default path (local cache), the alternative (live=True fetches from the API), and a prerequisite (run health_sync first to populate the cache). It also routes the agent to health_get_weight_readings for per-weigh-in granularity.

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