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Product Lookup by Barcode

product_lookup
Read-only

Look up a product by EAN/UPC barcode in Open Food Facts, Open Beauty Facts and Open Products Facts: name, brand, quantity, categories, ingredients, allergens, labels, nutrition per 100 g, Nutri-Score, NOVA group and image URL. Params: barcode (8 to 14 digits, required). Price: $0.005 USDC per call, paid inside this MCP call via x402 (USDC on Base, Solana, Polygon or Arbitrum). x402 MCP clients such as @x402/mcp pay automatically. Free sample: call with the example input {"barcode":"3017624010701"}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
barcodeYesEAN-13, EAN-8 or UPC

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.1/5.0
Behavior5/5

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

Beyond the annotations (readOnly/openWorld/non-destructive), it discloses a hard behavioral fact the agent must know: $0.005 USDC per call, settled inside the call via x402 on Base/Solana/Polygon/Arbitrum, with automatic payment for compatible clients. It also enumerates the returned fields in lieu of an output schema. This is exactly the kind of context annotations cannot carry.

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 purpose and scope, then params, then pricing, then a sample call — a sensible order with little waste. It is dense to the point of being a single run-on block, but nearly every clause carries operational value.

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?

With no output schema, the description compensates by listing the returned fields (name, brand, quantity, categories, ingredients, allergens, labels, nutrition, Nutri-Score, NOVA, image URL). Combined with the single-parameter schema, the pricing/auth model, and a worked example, an agent has everything needed to call it successfully.

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 already 100% (barcode: 'EAN-13, EAN-8 or UPC'), so the baseline is 3, but the description adds the 8-to-14-digit constraint and a concrete valid example input, which the schema does not provide.

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?

States a specific verb and resource ('look up a product by EAN/UPC barcode') and names the three source databases plus the fields returned, so the agent knows exactly what it gets. It does not, however, address the ambiguous sibling 'barcode' (likely a generator), so sibling differentiation is left to inference.

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 by the lookup-by-barcode framing, and the description usefully notes that x402 MCP clients pay automatically and that a free sample call is available. There is no explicit when-to-use vs when-not guidance and no named alternative among the many sibling lookup tools.

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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