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Garmin MCP Server

Garmin MCP Server

by JJRPF
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_heart_rates_summary

Retrieve a compact daily heart rate summary for any date. Provides essential metrics in about 500 bytes, ideal for daily health checkups and LLM integrations without bulky time-series data.

Instructions

Get heart rate summary with essential metrics (lightweight version)

Returns a compact summary (~500 bytes) instead of full time-series data (~25KB). Ideal for daily health checkups and LLM integrations.

Args: date: Date in YYYY-MM-DD format

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "date": "<date>"
    },
    "name": "get_heart_rates_summary"
  }
}

Input Schema

NameRequiredDescriptionDefault
dateYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.7/5.0
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses the output size (~500 bytes) and that it returns a compact summary. It does not mention error handling or missing data, but overall it is reasonably transparent for a read-only summary tool.

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 concise, with a front-loaded purpose and use case. It avoids unnecessary verbosity while still conveying the key differences from the full data tool.

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?

It provides enough context for an agent to decide when to use this tool versus get_heart_rates. It could specify what 'essential metrics' include, but that is not required for invocation. Given the simplicity of the tool, the description is nearly complete.

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?

The only parameter 'date' is given a clear format ('YYYY-MM-DD'), which is essential for correct invocation. Since the schema has no description for this parameter, the description adds necessary meaning beyond the schema.

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 action: 'Get heart rate summary with essential metrics' and clearly distinguishes it from the full time-series version with 'lightweight version' and 'compact summary'. The resource and verb are unambiguous.

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 says 'instead of full time-series data', which identifies when to use this tool over the fuller alternative. It also mentions 'Ideal for daily health checkups and LLM integrations', providing contextual use cases.

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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