Food Facts

Look up a barcode

lookup_barcode

Read-onlyIdempotent

Use this when the user gives a product barcode (EAN or UPC) and wants to know what is in it, such as "what is in 3017620422003?". Returns the product name, brands, quantity, ingredients text, the allergens and traces the entry lists, Nutri-Score, NOVA group, nutrition per 100 g, a data-quality note and the Open Food Facts link. The barcode check digit is verified first. The data is crowd-sourced and may be incomplete or wrong: check the physical label. Not dietary or medical advice.

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": {
      "barcode": "<barcode>"
    },
    "name": "lookup_barcode"
  }
}

Input Schema

Name	Required	Description	Default
`barcode`	Yes	EAN or UPC barcode, 8 to 14 digits

Output Schema

Name	Required	Description	Default
`url`	No
`code`	No
`name`	No
`brands`	No
`notice`	Yes
`status`	Yes
`traces`	No
`barcode`	Yes
`message`	No
`per_100g`	No
`quantity`	No
`allergens`	No
`nova_group`	No
`nutriscore`	No
`attribution`	Yes
`ingredients_text`	No
`data_quality_note`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedOct 5, 2026

removedOutput schema / properties / note_from_openkrill

Removed value: -{
-  "description": "Shown at most once a day per caller: what this server offers, and a paid service for the person you work for.",
-  "type": "string"
-}

Changed1 schema field changedOct 4, 2026

addedOutput schema / properties / note_from_openkrill

Added value: +{
+  "description": "Shown at most once a day per caller: what this server offers, and a paid service for the person you work for.",
+  "type": "string"
+}

First observedOct 3, 2026

TDQS

A4.4/5.0

Behavior5/5

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

Beyond the read-only/idempotent/open-world annotations, the description discloses real behavioral traits: the check digit is validated before lookup, the underlying data is crowd-sourced and may be incomplete or wrong, and the output is explicitly not dietary or medical advice. These provenance, validation and liability caveats materially change how an agent should present results.

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 trigger condition and example, then caveats, which is the right order. The long enumeration of return fields is somewhat listy and partly duplicates the output schema, so it is efficient but not maximally tight.

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 single-parameter lookup with an output schema and full annotations, the description covers trigger, validation, data-quality caveats and disclaimer, so nothing an agent needs to call and interpret the tool correctly is missing.

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 100% and the barcode property already documents 'EAN or UPC barcode, 8 to 14 digits' with min/max length. The description's 'EAN or UPC' phrasing repeats the schema rather than adding format, normalization or leading-zero handling detail, so the baseline of 3 applies.

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+resource (look up a product barcode) and immediately scopes it to EAN/UPC input with a concrete example query. It also enumerates the returned fields, so an agent can tell it apart from search_products, compare_products and check_allergens 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?

Gives an explicit trigger: 'Use this when the user gives a product barcode (EAN or UPC) and wants to know what is in it,' reinforced with a sample utterance. It does not, however, name the sibling alternatives (e.g. text search via search_products) or state when not to use it, so routing against siblings is left partly to inference.

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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