# nutriscan-ai

> Use this tool when you need to analyze food products and provide instant nutritional intelligence, allergen warnings, and diet compatibility checks. It solves problems such as identifying potential allergens, estimating health scores, and suggesting healthier alternatives through multi-modal input options like barcode, label photo, or ingredient text. With structured JSON outputs, it is ideal for AI agents requiring accurate and actionable food data in various contexts, including grocery shopping and meal planning.

Canonical page: https://skillsregistry.net/skills/b0d02xk-nutriscan-ai  
JSON: https://api.skillsregistry.net/v1/skills/b0d02xk-nutriscan-ai

## Description

Title: NutriScan AI — Food Intelligence & Allergen Guard

Short Description: A multi-modal food intelligence API for AI agents. Instantly analyze products via barcode, label photo, or ingredient text to get health scores, allergen warnings, and diet compatibility.

Long Description: NutriScan AI is a powerful Model Context Protocol (MCP) server that gives AI agents "eyes" and "expertise" in the grocery aisle. It bridges the gap between raw product data (Open Food Facts/USDA) and actionable nutritional intelligence.

Key Capabilities:
Multi-Modal Input: Seamlessly switch between barcode lookup (UPC/EAN), OCR-powered label image analysis, and raw ingredient list text.
Health Scoring: Instant Nutri-Score (A-F) grading and NOVA processing level classification (1-4).
Advanced Allergen Guard: Multi-stage detection for 10+ major allergen groups, using a proprietary blend of database tags, heuristics, and LLM reasoning to catch hidden derivatives.
Diet Compatibility: Automated verification for Vegan, Vegetarian, Keto, Paleo, Gluten-Free, Diabetic-friendly, Halal, and Kosher diets.
Smart Alternatives: Context-aware suggestions for healthier swaps when a product scores poorly.
Agent-Optimized: Designed specifically for AI agents (Claude, GPT, Cursor) with structured JSON outputs and descriptive tool schemas.

Use Cases:
"Scan this box of cereal and tell me if it's safe for a child with a peanut allergy."
"Analyze these ingredients and estimate the Nutri-Score."
"Is this snack compatible with a Paleo diet? If not, suggest a healthier swap."

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-05-12

## Source

- **Source listing:** [Smithery](https://smithery.ai/server/b0d02xk/nutriscan-ai)

## 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": "b0d02xk-nutriscan-ai"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/b0d02xk-nutriscan-ai` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/b0d02xk-nutriscan-ai/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