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delize

MyFitnessPal MCP Server

by delize

mfp_get_diary

Read-onlyIdempotent

Fetch a complete food diary for a specific date, including meals, portion sizes, nutritional breakdown, and daily totals/goals.

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

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A3.9/5.0
Behavior3/5

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

Annotations already disclose the full safety profile (readOnlyHint, idempotentHint, openWorldHint, destructiveHint=false), lowering the bar. The description adds some genuinely useful context: the markdown-vs-json output duality and the default-to-today behavior. But most of the prose enumerates return content (meals, entries, nutrition, totals, goals), which the existing output schema already documents, so the incremental behavioral disclosure is modest.

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-structured and front-loaded: purpose first, then return content, then Args, then Returns. It is slightly redundant — the trailing 'Returns: str: Formatted diary data with meals, entries, nutrition, and goals' restates the second prose paragraph, and the Args block partly mirrors schema descriptions — but at roughly 90 words the length is appropriate for a two-parameter read tool.

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 getter, the description plus the rich annotations (read-only, idempotent, non-destructive, open-world) plus the presence of an output schema give an agent everything needed to invoke it correctly. Minor gaps remain: behavior for dates with no diary entries and timezone semantics for 'today' are unspecified, which prevents a 5.

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?

The context signal reports 0% schema description coverage (the top-level 'params' wrapper property itself has no description), so the description carries the parameter-documentation burden. Its Args section compensates well: it documents the date format (YYYY-MM-DD), optionality, default-to-today behavior, and assigns semantics to the enum values ('markdown' for human-readable, 'json' for structured data) beyond the bare schema enum.

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+resource ('Get the food diary') with explicit scope ('for a specific date') and content ('all meals and their nutritional information'). The resource is unique among the sibling list — none of mfp_get_measurements, mfp_get_exercises, mfp_get_goals, or mfp_get_water could plausibly be confused with this — so an agent can select it correctly without opening the schema.

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

Usage Guidelines3/5

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

Usage context is implied by the purpose statement: an agent can infer this is the tool to call when it needs a full day's diary with meals and nutrition. However, the description gives no explicit when/when-not guidance and never names alternatives, even though siblings like mfp_get_report and mfp_get_food_details overlap in the food-reporting space.

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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