Canada's Food Guide MCP Server

Query Recipe Macros Table

query_recipe_macros_table

Retrieve recipe ingredients with matched Canadian Nutrient File nutrition values, serving sizes, and unit-match status so you can select servings and calculate macros.

Instructions

Query temp_recipe_macros table with joined CNF nutrition data for recipe calculations.

This tool retrieves recipe ingredients with their matched Canadian Nutrient File data, including nutrition values (calories, protein, fat, carbohydrates) for each available serving size. The data enables direct nutrition calculations using bulk_math_calculator without requiring database storage of intermediate results.

Returns recipe ingredient details, unit matching status, available CNF serving sizes, and complete CNF nutrition values per serving size for each ingredient. Unit matching status indicates: exact_match, conversion_available, manual_decision_needed, or no_cnf_data.

Use this tool to:

Get ingredient data with CNF nutrition values for each serving size
Review unit matching status and available serving options
Select appropriate serving sizes for nutrition calculations
Obtain complete data for bulk_math_calculator operations

Input Schema

Name	Required	Description	Default
`input_data`	Yes	Contains session_id, optional recipe_id filter, optional unit_match_status filter

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

Behavior4/5

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

With no annotations, the description carries the burden and does reasonably well: it enumerates the unit-matching states returned and frames the operation as a read that avoids database storage. It never explicitly states read-only/no side effects or what happens if the session has no data, leaving a modest gap for a mutation-free tool with an output schema.

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

Conciseness3/5

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

The purpose sentence is front-loaded and useful, but the four bullets largely restate the return contents already given in the paragraph above, and 'Returns recipe ingredient details...' repeats the opening. Trimming the redundant list would sharpen the definition.

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 read-only query with a full output schema and a single nested input object, the description covers purpose, returned fields, status semantics, and downstream workflow. It does not mention empty-session behavior or how filters interact, but nothing critical to invoking it is missing.

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%, so the filters (session_id, recipe_id, unit_match_status) are already documented in the schema and the description adds little beyond echoing the status values. The listed statuses also omit 'no_match', which the schema includes — a minor inconsistency the description could have resolved.

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?

The opening sentence gives a specific verb and resource ('Query temp_recipe_macros table with joined CNF nutrition data') and the body clarifies that it returns ingredients plus per-serving nutrition. This is clearly distinct from get_cnf_macronutrients_only or get_recipe, though the description never names a sibling to contrast with explicitly.

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 to:' list establishes concrete usage context (review unit matching, pick serving sizes, feed bulk_math_calculator), and the sentence about avoiding intermediate storage clarifies its place in the workflow. No when-not guidance or explicit alternative is given, which keeps it short of a 5.

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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