Cronometer MCP

import_recipe

Idempotent

Create a recipe from a free-text ingredient list by parsing each line into matching Cronometer foods and grams, with an optional preview before saving.

Instructions

Create a recipe from a free-text ingredient list.

Cronometer's own parser matches each line ("2 tbsp ketchup", "1 cup rice") to a database food and works out the grams, the same as Import Recipe in the app. Matching is fuzzy: show the matched ingredients to the user, and run with save=false first when unsure. create_recipe is the exact alternative when food ids and grams are already known.

Args: ingredients: One ingredient per line. name: Recipe name. Defaults to the one Cronometer suggests. servings: How many portions the batch makes. save: False to only parse and preview the matches.

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": {
      "ingredients": "<ingredients>"
    },
    "name": "import_recipe"
  }
}

Input Schema

Name	Required	Description	Default
`name`	No
`save`	No
`servings`	No
`ingredients`	Yes

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv2.1.0Nov 14, 2026

TDQS

A4.6/5.0

Behavior4/5

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

The annotations already declare non-read-only, open-world, idempotent, non-destructive, so the safety profile is covered. The description adds genuine behavior beyond that: matching is fuzzy, the parser resolves lines to database foods and derives grams, and save=false yields a parse-only preview. It does not mention rate limits or authentication, but for this tool the disclosed fuzzy-match and preview behavior is the meaningful risk context.

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

Conciseness4/5

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

It is front-loaded with the purpose, then the parser/fuzzy-match caveat and the alternative, then a compact Args block. Every sentence contributes, though the reference to 'the same as Import Recipe in the app' is mildly redundant and the Args formatting could be tighter.

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?

An output schema exists, so return values need no explanation. With that covered, the description supplies the parser behavior, the preview workflow, the sibling alternative, and all four parameter meanings — enough for an agent to call this correctly on the first attempt.

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?

Schema description coverage is 0%, so the description must carry the load, and the Args block documents all four parameters: ingredients is one per line, name defaults to Cronometer's suggestion, servings is the portion count, and save=false previews matches. It adds real meaning (format, default source, preview semantics) though it could be slightly more explicit about units or line syntax edge cases.

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 opens with a specific verb+resource: 'Create a recipe from a free-text ingredient list,' and explicitly distinguishes this tool from create_recipe ('the exact alternative when food ids and grams are already known'). An agent can tell which of the two recipe-creation tools to pick without opening either schema.

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?

It gives a concrete workflow rule — 'run with save=false first when unsure' — and names the alternative tool with the precise condition that selects it (food ids and grams known). Both when-to-use and when-to-use-something-else are stated.

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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