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Nutriscan MCP connector

Nutriscan MCP connector

by si-essence

allergens_additives

Read-only

Look up allergens, may-contain traces, additives (E-numbers), and a brief ingredients line by food barcode to answer allergy and ingredient questions.

Instructions

List allergens, may-contain traces, and additives (E-numbers) for one Open Food Facts product by barcode, plus a short ingredients line. Use for allergy and ingredient questions.

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": "allergens_additives"
  }
}

Input Schema

NameRequiredDescriptionDefault
barcodeYesBarcode printed on the package (EAN-8, UPC-A, or EAN-13). Digits only; spaces and dashes are ignored.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=true, so the safety profile is covered. The description adds useful payload context (that may-contain traces and an ingredients line are included, and that the source is Open Food Facts), but says nothing about behavior when a barcode is unknown or when allergen data is absent from the record.

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?

Two sentences, zero filler, with the returned data front-loaded and the use case placed after it. Nothing is repeated from the title or schema.

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?

With a single fully documented parameter, no output schema, and annotations covering the safety profile, the description supplies what an agent needs to call it: the source, the identifier, and the returned fields. The only meaningful gap is unspecified behavior for unknown barcodes or missing allergen data.

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 coverage is 100% and the barcode parameter is fully documented there, including accepted formats (EAN-8, UPC-A, EAN-13) and normalization of spaces and dashes. The description only restates that lookup is by barcode and adds the data source, so the schema is doing the heavy lifting — the baseline 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 ('List') plus the exact resources returned: allergens, may-contain traces, additives (E-numbers), and a short ingredients line, scoped to one Open Food Facts product by barcode. This is clearly distinguishable from siblings like nutrients_per_serving, nutriscore_nova, and barcode_lookup without opening any 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?

The sentence 'Use for allergy and ingredient questions' gives an explicit use context, which is more than most definitions offer. It stops short of naming alternatives or stating when not to use it (e.g., for full nutrition data use nutrients_per_serving), so it is clear but not complete routing guidance.

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