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Garmin MCP Lite

Garmin MCP Lite

by Golden0Voyager
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

garmin_body_composition

Reads weight and body-composition history from Garmin Connect to check existing daily entries and track trends before adding new measurements.

Instructions

Read weight and body-composition history from Garmin Connect.

Use this before garmin_add_body_composition to see whether a day already has an entry, and to answer trend questions ("did my body fat move").

Mass fields are converted to kilograms and null fields are omitted, so a record only carries the metrics that were actually measured. Most accounts only ever have weight_kg, because a scale that syncs weight alone (e.g. MyFitnessPal) never populates body fat, muscle mass or BMI.

Args: days: How many days back to look. Defaults to 90, capped at 730. limit: Maximum number of records to return, newest first. Defaults to 60.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "garmin_body_composition"
  }
}

Input Schema

NameRequiredDescriptionDefault
daysNo
limitNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.1.10

TDQS

A4.4/5.0
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 delivers real behavioral context: mass converted to kilograms, null fields omitted, records only carry metrics actually measured, and a realistic data-availability caveat (many accounts only have weight_kg due to weight-only scale syncs). It omits auth/permission requirements and any rate-limit or pagination-truncation behavior, so not fully exhaustive.

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-loaded with the verb+resource, then usage routing, then data behavior, then args — a sensible order with no filler sentences. The Args block restates the 90/60 defaults already present in the schema, which is mild redundancy, though the added 730 cap and newest-first ordering justify the section.

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-optional-parameter read tool with no annotations and no output schema, this covers filtering semantics, unit conversion, and null handling, which is most of what an agent needs. It does not describe the record shape beyond naming weight_kg (e.g. date field, other field names or units), which is the remaining gap given there is no output schema.

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: 'days' is documented as a lookback window capped at 730, and 'limit' is documented as a max record count returned newest-first. Both the bound and the ordering semantics are information the schema does not convey, fully closing the coverage gap.

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 ('Read weight and body-composition history from Garmin Connect'), which unambiguously separates it from the write-side sibling garmin_add_body_composition. The scope (history/trend, not a single day) is clear without opening the schema.

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?

Explicitly names the scenario ('before garmin_add_body_composition to see whether a day already has an entry') and a second use case ('answer trend questions'). It does not state when not to use it or point to other read siblings (e.g. garmin_hr_trend, garmin_weekly_stats), so it stops just short of a full routing rule.

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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