# Open Food Facts Nutrition Normalizer (`wakey7dev/open-food-facts-normalizer`) Actor

Search global Open Food Facts products with normalized brands, categories, allergens, nutrition per 100g, Nutri-Score, NOVA processing groups, and deduplicated barcodes.

- **URL**: https://apify.com/wakey7dev/open-food-facts-normalizer.md
- **Developed by:** [Chris Wakefield](https://apify.com/wakey7dev) (community)
- **Categories:** Business, AI
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per usage

This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-usage

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

![Chris The Dev](https://raw.githubusercontent.com/chriswakefield87/appstore-screenshot-translator/main/assets/actor-banner.png)

## Open Food Facts Nutrition Normalizer

Search the worldwide [Open Food Facts](https://world.openfoodfacts.org/) product database and receive clean, analysis-ready food records. The Actor deduplicates barcodes and normalizes brand names, category tags, allergens, country tags, packaging, nutrition units, Nutri-Score, and NOVA processing groups.

### Why use this Actor?

Raw food databases contain inconsistent casing, duplicate brand labels, multilingual tags, missing fields, and noisy category hierarchies. This Actor keeps the original product identity while returning consistent fields that are easier to use in nutrition apps, retail intelligence, catalogue enrichment, food safety research, and market analysis.

### Input parameters

| Parameter | Type | Description | Default |
|---|---|---|---|
| `searchQuery` | string | Product name or keyword, e.g. `coffee`, `cereal`, or `chocolate`. | `coffee` |
| `country` | string | Optional country tag such as `united-kingdom` or `united-states`. | — |
| `category` | string | Optional category tag such as `coffees` or `plant-based-foods`. | — |
| `maxResults` | integer | Maximum unique products, from 1 to 100. | `25` |

#### Example input

```json
{
  "searchQuery": "coffee",
  "country": "united-kingdom",
  "maxResults": 10
}
```

### Output

Each dataset item includes `barcode`, `productName`, `brandsNormalized`, `categoriesNormalized`, `allergensNormalized`, `nutriScore`, `novaGroup`, and a standardized `nutritionPer100g` object with energy, fat, sugars, fibre, protein, salt, and sodium where available. `sourceUrl` links back to the original product.

The run also writes:

- `OUTPUT`: a readable summary table
- `STATS`: machine-readable counts and Nutri-Score distribution
- `RESULTS`: the complete normalized result array

### Use cases

- Enrich retail and grocery product catalogues
- Build nutrition, allergen, or dietary discovery tools
- Compare brands and categories across countries
- Identify highly processed products using NOVA groups
- Prepare consistent food data for analytics and machine learning

### Data source and attribution

Data is retrieved live from the Open Food Facts API. Open Food Facts is a collaborative, open database of food products. Please review its [data licence and terms](https://world.openfoodfacts.org/terms-of-use) before redistributing results.

# Actor input Schema

## `searchQuery` (type: `string`):

Product name or keyword, such as coffee, cereal, or chocolate.

## `country` (type: `string`):

Optional Open Food Facts country tag, for example united-kingdom or united-states. Leave blank for all countries.

## `category` (type: `string`):

Optional category tag, for example coffees, cereals, or plant-based-foods.

## `maxResults` (type: `integer`):

Maximum unique products to return (1-100).

## Actor input object example

```json
{
  "searchQuery": "coffee",
  "country": "",
  "category": "",
  "maxResults": 25
}
```

# Actor output Schema

## `results` (type: `string`):

All normalized product records.

## `summary` (type: `string`):

Readable table of normalized products.

## `stats` (type: `string`):

Machine-readable counts and normalization statistics.

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "searchQuery": "coffee"
};

// Run the Actor and wait for it to finish
const run = await client.actor("wakey7dev/open-food-facts-normalizer").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "searchQuery": "coffee" }

# Run the Actor and wait for it to finish
run = client.actor("wakey7dev/open-food-facts-normalizer").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "searchQuery": "coffee"
}' |
apify call wakey7dev/open-food-facts-normalizer --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,wakey7dev/open-food-facts-normalizer"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/LPB7OyZYCrb7JyxVx/builds/fK0i81Ofhf8CUALdb/openapi.json