Cronometer MCP

list_biometrics

Read-onlyIdempotent

Lists every biometric metric type a Cronometer account can record, such as weight, body fat, heart rate, blood glucose, and sleep. Use the returned metric and unit IDs with get_biometrics to fetch readings.

Instructions

List the biometric metrics tracked in Cronometer.

Returns every metric type the account can record (Weight, Body Fat, Heart Rate, Blood Glucose, Waist Size, Sleep, blood panels, body measurements, etc.). Use the metric_id and a unit_id from the results with get_biometrics.

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": "list_biometrics"
  }
}

Input Schema

Name	Required	Description	Default
No arguments

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv2.1.0Nov 14, 2026

TDQS

A4.5/5.0

Behavior4/5

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

Annotations already define the read-only, idempotent, non-destructive nature. The description adds valuable behavioral context by disclosing that it returns 'every metric type the account can record' and that results contain metric_id and unit_id fields, enabling a follow-up workflow with get_biometrics. No contradiction with annotations.

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?

Three concise, information-dense sentences. The main purpose is front-loaded, followed by a clarifying example list and a practical usage pointer. No redundant words or repetition of schema/annotation content.

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?

For a parameterless list tool with rich annotations and an output schema, the description fully covers what the tool returns, gives concrete examples, and explains the subsequent step (get_biometrics). Nothing essential is missing.

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?

There are zero parameters, so the description is not required to explain parameter meaning. The baseline for zero-parameter tools is 4, and the description goes slightly beyond by indicating how to use the result fields (metric_id, unit_id), which adds semantic value even though not parameter-specific.

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 uses a specific verb ('List') with a clear resource ('the biometric metrics tracked in Cronometer'). It explicitly clarifies that this returns metric types (Weight, Body Fat, etc.), not actual measurements, which distinguishes it from get_biometrics (which retrieves actual biometric data). 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 clear context that this is a metadata-listing tool and explicitly instructs the agent to 'Use the metric_id and a unit_id from the results with get_biometrics.' It implies when to use it as a precursor to get_biometrics, though it does not explicitly state cases where it should NOT be used (e.g., when actual biometric values are needed).

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

Deploy Server