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JJRPF

Garmin MCP Server

by JJRPF

get_body_composition

Retrieve body composition metrics from Garmin Connect for a specified date or range. Supply a start date and optional end date to access body fat, muscle mass, and other health measurements.

Instructions

Get body composition data for a single date or date range

Args: start_date: Date in YYYY-MM-DD format or start date if end_date provided end_date: Optional end date in YYYY-MM-DD format for date range

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
end_dateNo
start_dateYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior3/5

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

No annotations are supplied, so the description carries the burden. It clearly frames this as a get/read operation and explains the date filtering behavior, but it does not disclose additional behavioral traits such as output granularity, units, or failure modes. Because this is a simple read tool and an output schema exists, the description is adequate but not rich.

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?

Two concise lines followed by a compact Args block. The main purpose is front-loaded and every sentence adds value.

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

Completeness4/5

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

For a two-parameter, read-only tool with an output schema, the description covers the operation and parameter relationships well. It barely misses full completeness because it does not explicitly differentiate from get_stats_and_body or state what body composition fields are returned, though the output schema may cover that aspect.

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

Parameters4/5

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

Schema description coverage is 0%, so the description must explain the parameters. It does: start_date is described as YYYY-MM-DD or range start, and end_date as an optional range end. This adds real meaning beyond the schema's type and required fields.

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 first sentence states a clear verb and resource: get body composition data, and adds the date/range scope. It does not explicitly distinguish itself from sibling get_stats_and_body or enumerate what body composition metrics are included, so it is clear but not maximally differentiated.

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

Usage Guidelines3/5

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

The date/range semantics imply when to use it, i.e., when retrieving body composition for one or more dates. However, there is no explicit when-to-use/when-not-to-use statement or comparison with sibling get_stats_and_body, which may also serve body composition needs.

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

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