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thesaaspreneur

MyFitnessPal MCP

mfp_get_diary

Read-onlyIdempotent

Get a food diary for any date, with meals, nutrition details, daily totals, and goals. Choose markdown or JSON output.

Instructions

Get the food diary for a specific date including all meals and their nutritional information.

Returns meals (Breakfast, Lunch, Dinner, Snacks) with each food entry's name,
quantity, and complete nutrition breakdown (calories, protein, carbs, fat, etc.).
Also includes daily totals and goals.

Args:
    params: GetDiaryInput containing:
        - date (str, optional): Date in YYYY-MM-DD format, defaults to today
        - response_format (str): 'markdown' or 'json'

Returns:
    str: Formatted diary data with meals, entries, nutrition, and goals

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Install Server

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already convey read-only, idempotent, and non-destructive behavior. The description adds useful behavioral detail by stating that date defaults to today, response_format controls output, and the result includes daily totals and goals. No contradiction with the annotations exists.

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 description is well-structured with a clear summary, Args, and Returns sections, keeping the core purpose in the first sentence. The Args section is somewhat redundant with the input schema, but the return details add value given the absence of an exposed output schema. There is no 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?

For a simple read-only retrieval tool, the description covers the essential inputs, default behavior, and expected return content. The annotations complete the safety profile. It is missing explicit usage guidance, but that gap is already reflected in the usage_guidelines score.

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 description coverage is reported as 0%, so the description carries the burden of explaining parameters. It explains date with format and default value, and response_format with allowed values and meaning. The only minor omission is not explicitly stating that response_format defaults to markdown, though the schema provides that.

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 description opens with a specific verb and resource: 'Get the food diary for a specific date including all meals and their nutritional information.' It clearly distinguishes this from sibling mutation tools like mfp_add_food_to_diary or mfp_delete_meal, and from other getters like mfp_get_goals or mfp_get_measurements. The resource is unambiguous even without naming alternatives.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives or when not to use it. There are no references to sibling getters, exclusions, or context about choosing markdown vs json for downstream tasks. An agent must infer usage purely from the tool name and description.

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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