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Unofficial Monsieur Cuisine MCP

Unofficial Monsieur Cuisine MCP

by githubllff
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

Restore Recipe

restore_recipe

Restore a trashed recipe to undo a deletion and bring it back as a draft.

Instructions

Restore a trashed recipe (undo delete_recipe), bringing it back as a draft.

delete_recipe only moves a recipe to "trash" and keeps its data, so this can undo it. The web app can't (it has no trash view), but the API allows it. The recipe comes back as a DRAFT no matter what it was before deletion, so if it was published, re-publish it with publish_recipe afterwards. Find trashed recipes to restore with list_my_recipes(status="trash").

Meaningful only on a trashed recipe: on an already-published recipe it fails (a live recipe can't be moved back to draft); on a draft it's a no-op.

Requires a saved login session: run uv run monsieur-cuisine-mcp-login once beforehand.

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": {
      "recipe_id": "<recipe_id>"
    },
    "name": "restore_recipe"
  }
}

Input Schema

NameRequiredDescriptionDefault
languageNoLocale, e.g. "pl-PL", "en-US".en-US
recipe_idYesNumeric id of the trashed recipe to restore.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.7/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and does so well: it discloses that deleted data is retained, that restoration always yields a DRAFT, that published recipes cannot be restored, that drafts are a no-op, and that a saved login session is required. These are exactly the behavioral traits an agent needs before invoking the tool.

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?

The core action and outcome are front-loaded, followed by practical context in short paragraphs. Every sentence adds useful information about undo semantics, resulting state, failure modes, discovery, or authentication; nothing is redundant.

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?

The description covers prerequisites, failure conditions, resulting state, follow-up actions, and how to locate valid inputs. An output schema exists, so return-value details need not be repeated, and the remaining behavioral context is thorough.

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 both parameters are already documented in the schema. The description reinforces that recipe_id must refer to a trashed recipe but adds no format or syntax details beyond the schema, and it does not mention the language parameter. Baseline 3 is appropriate.

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?

States a specific verb and resource ('Restore a trashed recipe') and immediately distinguishes it from delete_recipe by naming it as the undo operation. It also clarifies the resulting state (draft), making the tool's role unambiguous among siblings.

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?

Explicitly says when to use it, names the alternative (delete_recipe), explains how to find trashed recipes via list_my_recipes(status="trash"), and describes the follow-up publish_recipe step. It also states when it fails or is a no-op, leaving little to inference.

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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