Canada's Food Guide MCP Server

Compare Recipe Servings

compare_recipe_servings

Compare multiple recipes by servings, ingredients, or portions to plan meals, choose recipes by yield, and assess complexity or scaling needs.

Instructions

    Compare multiple recipes by servings, ingredients, or portion analysis.

    This tool analyzes multiple recipes side-by-side to help with meal planning,
    recipe selection, and understanding relative recipe sizes and complexity.

REMEMBER! Always share recipe url, and image_url, and title with users before returning full recipe details. This allows them to see the source and context of the recipe.

    Comparison types available:
    - 'servings': Compare serving counts and calculate ratios
    - 'ingredients': Compare ingredient counts and complexity
    - 'portions': Analyze per-portion implications and scaling

    Use this tool when:
    - Planning meals with consistent serving sizes
    - Choosing between similar recipes based on yield
    - Understanding recipe complexity before cooking
    - Calculating ingredients needed for meal prep
    - Comparing homemade vs store-bought portions

    Args:
        comparison_input: Contains session_id, list of recipe_ids to compare,
                         and comparison_type ('servings', 'ingredients', or 'portions')

    Returns:
        Dict with comparative analysis including recipe details, serving ratios,
        ingredient complexity comparison, and recommendations for scaling,
        or error message if recipes not found or comparison fails

Input Schema

Name	Required	Description	Default
`comparison_input`	Yes	Input model for comparing recipes by servings or ingredients

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv3.0.0Nov 4, 2026

TDQS

A3.8/5.0

Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It does disclose failure behavior ('error message if recipes not found or comparison fails') and reuses the session_id as a prerequisite, but never states that the operation is read-only, whether it mutates session state, or any permission requirements for the recurring 'REMEMBER!' instruction to share url/image_url/title.

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?

Well front-loaded: purpose, then workflow note, then comparison types, then when-to-use, then Args/Returns. Slight redundancy remains because the Args and Returns blocks restate what the input and output schemas already declare, and the shouting 'REMEMBER!' line interrupts the flow.

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?

For a nested-input tool with an output schema, the definition supplies the prerequisite (a session containing the recipes), the mode semantics, and the analysis dimensions returned. The only meaningful gap is the absence of any guardrail about whether comparing writes to or only reads from the session.

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 coverage is 100%, so the baseline would be 3, but the description adds real meaning by explaining what each comparison_type actually computes: 'servings' calculates ratios, 'ingredients' compares counts and complexity, 'portions' analyzes per-portion scaling. The default of 'servings' and the multi-recipe intent are also reinforced in prose.

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

Purpose4/5

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

States a specific verb and resource ('Compare multiple recipes by servings, ingredients, or portion analysis') and enumerates the three comparison modes. It does not explicitly name the nearest sibling (scale_recipe_servings) to draw the line between comparing and rescaling, so it falls just short of the top band.

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?

A five-bullet 'Use this tool when' list gives concrete scenarios (meal planning with consistent serving sizes, choosing between similar recipes by yield, pre-cook complexity checks). It lacks any when-not guidance or a pointer to alternatives such as scale_recipe_servings or calculate_recipe_nutrition_summary, so the agent must infer exclusions.

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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