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garmin-mcp

garmin-mcp

by Lander-garmin
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

get_devices

Check registered Garmin devices and their last sync time to verify data freshness and avoid relying on stale intraday values.

Instructions

Registered Garmin devices and the last-used device with its last sync time.

Use this to know how fresh the data is: if the watch has not synced recently, intraday values will be stale.

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": "get_devices"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
dataNoCompacted Garmin payload; null if unavailable.
noteNoExplains missing data or truncation.
paramsNoParameters used.
sourceYesGarmin Connect API method the data came from.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.5/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses the tool's output (registered devices, last-used device, last sync time) and adds behavioral context about data freshness implications. It does not explicitly state read-only, but the nature of 'get' plus the informational content implies a non-mutating operation. The added freshness context goes beyond a bare listing.

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?

The description is two sentences, with the core result stated first and the usage guidance second. Every sentence earns its place, no fluff, and the key information is front-loaded.

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?

Given the tool has no parameters and an output schema exists (as indicated by context signals), the description fully covers what the tool does and why it matters. It explains the freshness implication, which is the main contextual value. There is no missing information that an agent would need to call this tool correctly.

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?

The tool has zero parameters, so the description does not need to explain any. According to the rubric, a zero-parameter tool gets a baseline of 4. The description adds no parameter-related info, but none is required.

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?

The description states a specific verb and resource: 'Registered Garmin devices and the last-used device with its last sync time.' It clearly identifies what the tool returns and is distinct from sibling tools that focus on individual metrics like sleep, steps, or heart rate. The purpose is unambiguous.

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?

The description provides explicit guidance on when to use the tool: 'Use this to know how fresh the data is.' It explains the consequence of stale sync (intraday values will be stale), which directly helps an agent decide to call this before other data tools. It doesn't mention alternatives, but there is no sibling with a similar purpose, so the guidance is sufficient.

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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