Skip to main content
Glama
JagjeevanAK

OpenFoodFacts-mcp

by JagjeevanAK

getProductInsights

Retrieve AI-powered insights for food products including detected labels, categories, ingredient issues, and more. Filter by barcode, country, or insight type to analyze product data.

Instructions

Get AI-generated insights about products (detected labels, categories, ingredients issues, etc.)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
barcodeNoFilter by product barcode
insightTypeNoType of insight to retrieve
countryNoFilter by country
countNoNumber of insights to return
pageNoPage number
Behavior2/5

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

No annotations exist, so description must disclose behavioral traits. It mentions 'AI-generated' but does not explain performance implications, required permissions, or how parameters affect 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?

Single sentence is concise and front-loaded with the core action. No wasted words, but could be slightly more structured with bullet examples.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Does not describe return format, pagination behavior, or how multiple parameters combine. With no output schema, this is a significant gap.

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%, so description adds no extra meaning beyond what the schema already provides. Baseline 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?

Clearly states the tool retrieves AI-generated insights about products and lists examples like labels and categories, which distinguishes it from sibling tools like getProductByBarcode or analyzeProduct.

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

Usage Guidelines2/5

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

No guidance on when to use this tool versus other insight-related tools (e.g., getInsightTypes, analyzeProduct) or when to avoid it. No context provided.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/JagjeevanAK/OpenFoodFacts-MCP'

If you have feedback or need assistance with the MCP directory API, please join our Discord server