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domdomegg

openfoodfacts-mcp

Get product

get_product
Read-only

Retrieve current product data from Open Food Facts by barcode. Direct database access ensures up-to-date nutrition and ingredient information.

Instructions

Get product information from Open Food Facts by barcode. Reads the primary database directly (no sync lag), so this is always current even when search_products returns stale results. Prefer this over search whenever you have a barcode. If this returns "product not found", the product genuinely isn't in the database — you can add it with add_or_edit_product.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fieldsNoFields to return. By default ALL fields are returned — nothing is omitted, so a field is never misleadingly null/absent just because it wasn't requested (e.g. `images` is always populated when the product has images). Pass an explicit list only to narrow the otherwise-verbose response.
barcodeYesProduct barcode (EAN-13, UPC-A, etc.)
languageNoLanguage code for language-dependent fields (product_name, generic_name, ingredients_text). Defaults to "en". When a product has a different primary language, the unsuffixed field names return that language's data — this param ensures you get the language you want.en
Behavior4/5

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

Annotations already declare readOnlyHint=true. Description adds valuable context: reads primary database (no sync lag), always current, and explains behavior on 'product not found'. Only lacks detail on exact return format.

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?

Four sentences, each essential. Front-loaded with purpose, then usage guidance, then edge-case handling. No wasted words.

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?

Covers key aspects: what the tool does, when to use, behavior on missing product, and parameter nuances. Lacks specification of return fields beyond examples in parameters, but overall adequate for tool usage.

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

Parameters4/5

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

Schema coverage is 100%. Description enhances understanding: explains default behavior for 'fields' (all returned by default) and clarifies 'language' parameter's role in handling primary language. Adds value beyond schema.

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 clearly states the tool retrieves product information by barcode from Open Food Facts. It distinguishes itself from sibling tools like search_products and add_or_edit_product by emphasizing direct database reads and freshness.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicit guidance: 'Prefer this over search whenever you have a barcode' and explains fallback to add_or_edit_product if not found. No ambiguity about when to use.

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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