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garmin-mcp

garmin-mcp

by konstantintutsch
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

get_race_predictions

Read-only

Retrieve predicted race times for 5K, 10K, half marathon, and marathon for today or a specified date range from Garmin Connect.

Instructions

Return race predictions for the 5k, 10k, half marathon and marathon. Accepts either 0 parameters or all three: If all parameters are empty, returns the race predictions for the current date Or returns the race predictions for each day or month in the range provided. (Garmin Connect, read-only. Dates are YYYY-MM-DD.)

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_race_predictions"
  }
}

Input Schema

NameRequiredDescriptionDefault
enddateNo
startdateNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.3/5.0
Behavior4/5

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

The annotations already establish read-only, non-destructive, open-world behavior, and the description usefully adds 'Garmin Connect, read-only' plus the distinction between empty-input behavior and range behavior. It adds meaningful context beyond the annotations, though it does not discuss pagination or result volume.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short and front-loads the core purpose, but the sentence structure is awkward and the incorrect 'all three' phrasing creates a needless inconsistency. It is reasonably sized but not cleanly structured.

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

Completeness3/5

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

An output schema exists, so return-value detail is not required, and the annotations cover safety. Still, for a tool with zero schema description coverage and a real parameter-count mismatch, the description is only minimally sufficient for correct invocation.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must carry parameter meaning. It does mention the YYYY-MM-DD format and range behavior, but it never clearly maps meaning to `startdate` and `enddate`, and it incorrectly refers to 'all three' parameters when the schema has only two.

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 description states a specific verb and resource: 'Return race predictions' for four named race distances. It is clear what the tool does, though it does not explicitly differentiate itself from the many sibling read tools beyond the unique race-prediction subject matter.

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?

It gives usable invocation guidance: call with no parameters for the current date, or provide a date range for per-day/per-month predictions. However, it says 'all three' parameters even though the schema defines only two, which introduces avoidable confusion and reduces confidence in the usage instructions.

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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