Canada's Food Guide MCP Server

Scale Multiple Ingredients

scale_multiple_ingredients

Scale multiple recipe ingredients by different factors in one operation to customize recipes, adjust macro ratios, or meet dietary needs.

Instructions

Scale multiple ingredients with different factors in a single operation.

This tool enables complex recipe modifications by applying different scaling factors to different ingredients simultaneously. Useful for recipe development, dietary customization, or creating recipe variations.

The scaling process:

Matches each ingredient name to recipe ingredients (partial matching)
Applies individual scale factors to each matched ingredient
Processes all scalings in a single transaction
Reports success and failure for each ingredient
Maintains ingredient order and relationships

Use this tool when:

Creating low-sodium versions (reduce salt, increase herbs)
Adjusting macro ratios (increase protein, reduce carbs)
Developing recipe variations with multiple changes
Customizing recipes for dietary restrictions
Batch processing multiple ingredient adjustments

Input Schema

Name	Required	Description	Default
`bulk_input`	Yes	Contains session_id, recipe_id, and ingredient_scales dict mapping ingredient names (partial matches allowed) to scale factors

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv3.0.0Nov 4, 2026

TDQS

A4.1/5.0

Behavior4/5

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

With no annotations, the description carries the behavioral burden and supplies meaningful detail: partial name matching, per-ingredient factors, single-transaction processing, per-ingredient success/failure reporting, and preservation of ingredient order and relationships. It does not clarify whether the session recipe is persistently overwritten, how ambiguous matches are resolved, or whether a failure rolls back other scalings.

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 purpose is front-loaded, and the process and use-case bullets are easy to scan. The second paragraph and several closing use-case bullets repeat the opening idea, making the definition somewhat longer than necessary.

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?

Together with the fully described nested input schema and the output schema, the description is sufficient for most calls and explains the important bulk-operation behavior. For a session-based mutation without annotations, it still omits session/recipe prerequisites, numeric factor conventions, and precise ambiguity and failure semantics.

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 coverage is 100%, and the description largely restates the documented name-to-factor mapping and partial matching. Its examples explain why different factors might be used, but it adds no numeric conventions such as 0.5 halving an ingredient or 2 doubling it, factor constraints, or match-selection guidance.

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 opening line gives a precise verb, resource, and scope: scaling several recipe ingredients with different factors in one operation. That scope distinguishes it in substance from scale_individual_ingredient and scale_recipe_servings, even though those siblings are not named.

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 'Use this tool when' section provides concrete contexts, including dietary customization, macro-ratio adjustment, and recipe variation development. It lacks explicit when-not guidance and does not route single-ingredient or uniform whole-recipe scaling to the appropriate sibling tools.

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

Deploy Server