# Open Food Facts MCP Server

> Use this tool when you need to access detailed food product information, nutritional data, and environmental scores to inform users' food choices. It solves problems such as product identification, nutritional analysis, and dietary recommendation by providing inputs like barcode or search queries and outputs like product details and comparison results. It is ideal for use cases involving smart search, filtering, and product comparison to enable informed decision-making.

Canonical page: https://skillsregistry.net/skills/caleb-conner-open-food-facts-mcp  
JSON: https://api.skillsregistry.net/v1/skills/caleb-conner-open-food-facts-mcp

## Description

Enables AI assistants to access the Open Food Facts database to query detailed food product information, nutritional data, and environmental scores. Supports product lookup by barcode, smart search with filtering, nutritional analysis, product comparison, and dietary recommendations to help users make informed food choices.

## Trust

- **Trust score (0–1):** 0.92
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-09-19

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/am4m4ez5g7)
- **Repository:** <https://github.com/caleb-conner/open-food-facts-mcp>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "caleb-conner-open-food-facts-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/caleb-conner-open-food-facts-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/caleb-conner-open-food-facts-mcp/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt