MyFitnessPal MCP Server

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mfp_set_water

Set a day's total water intake in MyFitnessPal using milliliters or cups, optionally for a specific date; the value replaces, not adds to, that day's total.

Instructions

Log water intake for a specific date.

Sets the day's total water. MyFitnessPal stores water in millilitres, so pass milliliters (preferred) or cups (converted at 236.588 ml/cup). The value replaces the day's total rather than adding to it.

Args: params: SetWaterInput containing: - milliliters (float, optional): Total ml for the day - cups (float, optional): Total US cups for the day - date (str, optional): Date in YYYY-MM-DD format, defaults to today

Returns: str: Confirmation message with the logged water amount

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "params": "<params>"
    },
    "name": "mfp_set_water"
  }
}

Input Schema

Name	Required	Description	Default
`params`	Yes

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed8 schema fields changedv1.4.0Nov 4, 2026

addedInput schema / $defs / SetWaterInput / properties / cups / anyOf

Added value: +[
+  {
+    "maximum": 60,
+    "minimum": 0,
+    "type": "number"
+  },
+  {
+    "type": "null"
+  }
+]

addedInput schema / $defs / SetWaterInput / properties / cups / default
```
Added value: +null
```

changedInput schema / $defs / SetWaterInput / properties / cups / description

Previous value: -"Number of cups of water (e.g., 2.5 for 2.5 cups). Note: MyFitnessPal uses cups as the unit."New value: +"Total water for the day in US cups (1 cup = 236.588 ml). Legacy alternative to milliliters. Replaces the day's total."

removedInput schema / $defs / SetWaterInput / properties / cups / maximum
```
Removed value: -50
```
removedInput schema / $defs / SetWaterInput / properties / cups / minimum
```
Removed value: -0
```
removedInput schema / $defs / SetWaterInput / properties / cups / type
```
Removed value: -"number"
```

addedInput schema / $defs / SetWaterInput / properties / milliliters

Added value: +{
+  "anyOf": [
+    {
+      "maximum": 15000,
+      "minimum": 0,
+      "type": "number"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "description": "Total water for the day in millilitres (e.g. 1300 for 1.3 L). Preferred. Replaces the day's total, it does not add to it.",
+  "title": "Milliliters"
+}

removedInput schema / $defs / SetWaterInput / required
```
Removed value: -[
-  "cups"
-]
```

First observedv0.1.0Sep 6, 2026

TDQS

A3.8/5.0

Behavior4/5

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

Adds genuinely useful behavior beyond the annotations: the value replaces rather than accumulates the day's total, and the ml/cup conversion factor is spelled out. This is the critical fact an agent needs before calling, since destructiveHint=false might otherwise suggest an append. Minor tension: a total-replacing set is naturally idempotent, yet idempotentHint=false is declared, which the description does not reconcile.

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?

Front-loaded with the operation and its key replace-semantics before the Args/Returns scaffolding, and no sentence is filler. The Args section duplicates schema text, costing a little density, but the structure is easy to scan.

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

Completeness3/5

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

An output schema exists, so the brief Returns line is sufficient, and the mutation semantics are covered. The remaining gap is conflict handling between the two interchangeable unit fields and any permission or failure behavior for an openWorld write, neither of which is addressed.

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?

The Args block enumerates all three fields with types, defaults, and format, which compensates for the reported low schema description coverage. However, the wording largely restates what the schema already says ("Preferred", "Replaces the day's total", the 236.588 factor), so it adds little new meaning. It never states what happens when both milliliters and cups are supplied, which is the one precedence question the schema does not answer either.

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 and resource ("Log water intake") plus the scope ("for a specific date") and immediately clarifies the write semantics with "Sets the day's total water." Against siblings that are all mfp_get_* readers, an agent can tell this is the write counterpart without opening either 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 is implied rather than stated: the agent learns it should supply milliliters or cups, but there is no explicit when-to-use vs when-not guidance, no mention of verifying with mfp_get_water first, and no note on prerequisites such as an authenticated session. The tool's purpose is obvious enough that this is adequate but leaves routing to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.