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thesaaspreneur

MyFitnessPal MCP

mfp_set_measurement

Log today's body measurements like weight or body fat in MyFitnessPal. Enter the measurement type and value to track your progress.

Instructions

Log a new body measurement (weight, body fat, etc.) for today.

Records the measurement value in MyFitnessPal for tracking progress.

Args:
    params: SetMeasurementInput containing:
        - measurement (str): Type of measurement (default 'Weight')
        - value (float): Measurement value (e.g., 185.5)

Returns:
    str: Confirmation message with the logged value

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Install Server

TDQS

A4.1/5.0
Behavior3/5

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

Annotations already set readOnlyHint=false and destructiveHint=false, so the write nature is known. The description adds the 'for today' temporal constraint, which is useful. However, it does not disclose what happens if a measurement already exists for today (overwrite vs. duplicate), nor any permission/authentication nuances. Since the description does not contradict annotations, a 3 is appropriate.

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 compact: two introductory sentences plus a structured Args/Returns section. The phrase 'Records the measurement value in MyFitnessPal for tracking progress' is slightly redundant with the first sentence, but it adds context about where data goes. No fluff, and the essential info is front-loaded.

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 one-parameter tool with an output schema, the description covers purpose, params, and return format. It omits edge cases (e.g., handling duplicate logs) but those are minor for a straightforward logging action. The output schema covers return values, so no need to detail them. Overall, an agent can call this correctly based on the description alone.

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 Args block explicitly lists 'measurement' with default 'Weight' and 'value' with an example (185.5). Even though the schema properties have descriptions, the context signal indicates 0% coverage, so the description compensates well. It clarifies the value is the numeric measurement and that measurement type is optional with a default. This adds meaning beyond the schema's JSON structure.

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 clearly states 'Log a new body measurement (weight, body fat, etc.) for today.' It identifies the verb (log), the resource (body measurement), and the scope (today). Among 30+ sibling tools, this is distinct from set_water, set_goals, and log_exercise, so an agent can easily differentiate it 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 Guidelines4/5

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

The description implies the use case: recording a measurement for today. It gives no explicit when-not-to-use or alternatives, but the context is clear enough given the sibling names (e.g., get_measurements for reading). A small gap: it does not mention scenarios like replacing an existing entry.

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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