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AdamWalt

MyFitnessPal MCP Server

by AdamWalt

mfp_set_water

Set water intake for a day by specifying cups consumed. Accepts a date, defaulting to today, to log hydration in MyFitnessPal.

Instructions

Log water intake for a specific date.

Sets the number of cups of water consumed for the day. MyFitnessPal uses
cups as the unit (1 cup = ~237ml).

Args:
    params: SetWaterInput containing:
        - cups (float): Number of cups of water (e.g., 2.5 for 2.5 cups)
        - date (str, optional): Date in YYYY-MM-DD format, defaults to today

Returns:
    str: Confirmation message with the logged water amount

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Beyond the annotations, the description adds useful context: the cups-to-milliliters conversion, the optional date defaulting to today, and the return confirmation. It does not explicitly state whether setting overwrites existing values, but 'set' strongly implies replacement, and there is no contradiction with annotations.

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

Conciseness5/5

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

The description is compact and well-organized with a short intro, an Args block, and a Returns line. Every sentence adds value—unit conversion, default behavior, and return type—with no redundancy or fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple setter tool, the description covers all essential aspects: what it does, parameter semantics, unit conversion, date default, and the confirmation return. An output schema exists, so the return description is a helpful addition rather than a necessity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The Args section fully documents both parameters: cups as a float with an example, and date as an optional YYYY-MM-DD string with a default. This compensates for the opaque top-level params schema and adds practical usage detail.

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 uses specific verbs 'Log' and 'Sets' with a clear resource ('water intake') for a specific date. It also includes the unit and distinguishes itself from sibling read tools like mfp_get_water.

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 clearly states the action ('Log water intake') and the date default behavior, implying when to use it. However, it does not explicitly name alternatives or exclusions, so it stops 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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