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Cronometer MCP Server and API by Cotlet

Get nutrition summary in Cronometer

cronometer_get_nutrition_summary
Read-onlyIdempotent

Get nutrition summary in the user's own Cronometer account from ChatGPT, Claude or any AI agent. Returns how to do it in Cronometer step by step (screens, buttons, fields) and opens nothing by itself; then do it with the cotlet_browser_* tools in the user's Cronometer Cloud Browser. Cronometer's official API: Cronometer has no public API (checked 5 Nov 2026).

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": "cronometer_get_nutrition_summary"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

B3.4/5.0
Behavior4/5

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

Beyond the readOnly/idempotent annotations, the description states two genuinely useful facts: the tool "opens nothing by itself" (no side effects, purely instructional output) and that Cronometer has no public API. That prevents an agent from expecting direct data access. It could go further by describing the shape of the returned guide, but the added context is substantive.

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 core information (returns a guide, opens nothing, then use browser tools) is present but buried in a run-on sentence, and the phrase "from ChatGPT, Claude or any AI agent" adds no operational value. The trailing API note with a dated check is only marginally relevant.

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?

For a zero-parameter, read-only helper with no output schema, the essential mechanics are covered: what it returns and what to do next. What is missing is any sense of the summary's content or structure (macros, targets, timeframe), which matters because the name implies data the tool does not actually deliver.

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 takes zero parameters, so there is nothing for the description to disambiguate. Baseline 4 applies; no parameter-related gaps exist.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description does reveal the real behavior — it returns a step-by-step how-to rather than data — but the opening sentence ("Get nutrition summary in the user's own Cronometer account") reads like a data-retrieval tool and only the mid-sentence clause corrects that. It never distinguishes itself from siblings like cronometer_get_diary_day that presumably return actual nutrition data, leaving the agent to infer which one yields numbers.

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 a clear follow-up path: after reading the guide, perform the steps with the cotlet_browser_* tools in the user's Cronometer Cloud Browser. It stops short of saying when to prefer this over a direct data tool such as cronometer_get_diary_day, so the when-to-use decision versus alternatives is only implied.

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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