Unofficial Monsieur Cuisine MCP

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Get Paprika Recipe

get_paprika_recipe

Preview how a single Paprika recipe converts to a Monsieur Cuisine Smart recipe without creating anything, so you can review tricky mappings before importing.

Instructions

Preview how ONE recipe from a Paprika export converts to a Monsieur Cuisine Smart recipe, without creating anything.

Returns the parsed Paprika fields plus the converted payload: ingredients split into amount/unit/name, direction sentences mapped onto device programs (Thermomix "3 sec/speed 7" -> customized, "5 min/120°C/speed 1" -> customized, "212°F/reverse speed 1" -> customized reverse, "weigh 50 g" -> scale, oven/simmer notation -> roasting/slow_cooking/steaming/kneading), mapped category/complexity ids, parsed servings/times/nutrition, and the extracted cover-image file. Review a tricky conversion here, fix it with create_recipe/edit_recipe if needed - or skip straight to import_paprika_recipes, which does the same conversion automatically.

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": {
      "zip_path": "<zip_path>",
      "name": "<name>"
    },
    "name": "get_paprika_recipe"
  }
}

Input Schema

Name	Required	Description	Default
`name`	Yes	Recipe-name substring, e.g. "Arrabbiata".
`language`	No	Locale, e.g. "en-US".	en-US
`zip_path`	Yes	Path to the .paprikarecipes.zip export file.

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Oct 23, 2026

TDQS

A4.3/5.0

Behavior4/5

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

With no annotations, the description carries the full burden and does well: it declares the operation non-mutating and enumerates what the response contains (parsed fields, converted payload, mapped program/category ids, parsed servings/times/nutrition, cover image) plus concrete conversion rules. It does not say how ambiguity is handled, e.g. what happens if the name substring matches zero or several recipes, nor whether an export file must be previously uploaded.

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?

The key constraint and non-mutation guarantee are front-loaded in the first sentence, and the parenthetical mapping examples justify their length by telling the agent what conversion output to expect. The nested program-mapping list is dense but each item is concrete rather than filler.

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?

An output schema exists, so the description need not re-specify return values, yet it helpfully summarizes them. The main remaining hole is selection semantics: an agent cannot tell from the description what happens when the name substring matches multiple recipes or none, which matters given this is a 'preview one' tool.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already documents zip_path, name and language. The description adds only the emphasis that exactly ONE recipe is resolved, without explaining substring-matching behavior or multi-match resolution, so the baseline 3 applies.

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 first sentence gives a specific verb (preview) and resource (ONE recipe from a Paprika export) and explicitly negates mutation ('without creating anything'). It is immediately distinguishable from list_paprika_recipes (listing) and import_paprika_recipes (bulk conversion with creation), both named in the text.

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 states the selecting condition precisely: review a tricky conversion here, repair with create_recipe/edit_recipe, or skip straight to import_paprika_recipes which does the same conversion automatically. Both the alternative and the criterion that picks it are given, leaving nothing to inference.

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