Skip to main content
Glama
AiAgentKarl

nutrition-mcp-server

tool_calculate_daily_intake

Calculate the percentage of daily nutritional needs covered by a food item using its USDA ID, number of servings, and serving size in grams.

Instructions

Berechnet wie viel Prozent des Tagesbedarfs ein Lebensmittel deckt.

Args: fdc_id: USDA FoodData Central ID servings: Anzahl der Portionen (Standard: 1) serving_grams: Groesse einer Portion in Gramm (Standard: 100g)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fdc_idYes
servingsNo
serving_gramsNo
Behavior2/5

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

No annotations are present, so the description carries full burden. It does not disclose any behavioral traits such as API calls, rate limits, or side effects. Only the basic operation is stated.

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 two concise sentences plus an Args section. Every word is necessary and there is no filler.

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

Completeness2/5

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

For a 3-parameter tool with no output schema or annotations, the description lacks details about the return value (e.g., format, units) and how daily values are determined. Missing context for new users.

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?

Schema description coverage is 0%, but the description lists each parameter with brief context (e.g., 'USDA FoodData Central ID' for fdc_id). This adds value beyond the schema, but details like allowed ranges or examples are missing.

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 states that the tool calculates the percentage of daily requirement a food covers, using a specific verb 'Berechnet' and resource 'Tagesbedarfs'. This clearly distinguishes it from sibling tools like tool_get_nutrition_facts (raw nutrient values) and tool_compare_foods (comparison).

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. There is no mention of prerequisites, exclusions, or context for when this tool is appropriate.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/AiAgentKarl/nutrition-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server