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lzinga

US Government Open Data MCP

fooddata_search

Read-only

Search the USDA FoodData Central database by keyword to find foods with basic nutrient information. Filter by data type, brand, and more.

Instructions

Search the USDA FoodData Central database for foods by keyword. Returns matching foods with basic nutrient info. Covers 300K+ foods including branded products.

Data types: 'Foundation' (generic whole foods), 'SR Legacy' (historical USDA reference), 'Branded' (commercial products with UPC), 'Survey' (FNDDS dietary studies).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesFood search term (e.g. 'chicken breast', 'cheddar cheese', 'apple')
dataTypeNoFilter by data type
brandOwnerNoFilter by brand owner for branded foods (e.g. 'Kraft', 'General Mills')
pageSizeNoResults per page (default 25, max 200)
pageNumberNoPage number (1-based)
sortByNoSort field
sortOrderNoSort direction
Behavior4/5

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

Annotations already declare readOnlyHint=true. The description adds meaningful context beyond this: it mentions the return of basic nutrient info, coverage of 300K+ foods, and lists the four data types. No contradictions or missing behavioral details that are essential for safe use.

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 three sentences, front-loaded with the core action, and every sentence adds value. It efficiently covers purpose, return content, coverage, and data types without any waste.

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?

Given the tool has 7 parameters (1 required), 100% schema coverage, and no output schema, the description adequately explains scope, coverage, and data types. It does not explain pagination behavior, but those details are in the schema, and the description is sufficient for an agent to understand the tool's overall capabilities.

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 input schema has 100% coverage with descriptions for all 7 parameters. The tool description does not add significant extra meaning beyond what the schema already provides; it only reiterates the data types. Baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it searches the USDA FoodData Central database by keyword, returns matching foods with basic nutrient info, and covers 300K+ foods including branded products. However, it does not explicitly distinguish itself from sibling tools like fooddata_detail or fooddata_list, which could serve similar purposes.

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?

The description implies the tool should be used for keyword-based food searches, but it provides no explicit guidance on when not to use it or mentions alternatives (e.g., when an FDC ID is available). Usage is implied but not clearly differentiated.

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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