Open Food Facts Scraper — Nutrition, NutriScore & Barcodes | from $0.50/1K

Built for nutrition-app developers, food-tech teams, and LLM pipelines that need structured product data by barcode (EAN-13, UPC) or keyword — NutriScore, NOVA group, allergens, and 25+ fields per product. Official Open Food Facts API, no proxy, no auth.

Scrape food product data from Open Food Facts via the official public API. Lookup products by barcode (EAN-13, UPC) or full-text search. Returns a flat, analysis-ready record per product.

What you get per product

Field	Example
barcode	737628064502
product_name	Thai peanut noodle kit
brands	Simply Asia
nutriscore_grade	d
nova_group	4 (1=unprocessed → 4=ultra-processed)
ecoscore_grade	c
energy_kcal_100g	385.0
fat_100g, saturated_fat_100g	7.69, 1.5
sugars_100g, fiber_100g	13.46, 2.1
proteins_100g, salt_100g	8.3, 0.72
ingredients_text	Rice Noodles (rice, water)...
categories	["plant-based-foods", "pastas"]
allergens	["peanuts", "soybeans"]
labels	["organic", "gluten-free"]
countries	["france", "united-states"]
image_url	https://images.openfoodfacts.org/...
url	https://world.openfoodfacts.org/product/...
parse_confidence	0.95

Use cases

• Nutrition apps — bulk-import product data by barcode list
• Diet trackers — filter by NutriScore or NOVA group
• Food research — export full ingredient & allergen data for analysis
• Retail / e-commerce — enrich product catalog with nutrition info
• Price comparison apps — add nutritional context to product listings

Input

{
  "barcodes": ["737628064502", "3017620422003"],
  "searchQueries": ["organic yogurt", "gluten free pasta"],
  "maxItems": 200,
  "language": "en",
  "pageSize": 50,
  "skipNotFound": true
}

Why this scraper?

• Official API — no scraping, no blocks, 100% reliable
• Full nutritional panel — competitors return <10 fields; we return 25+
• NutriScore + NOVA + Eco-Score in one record
• Pagination — search results paginated automatically up to maxItems
• Confidence tracking — every record includes parse_confidence and warnings so you know immediately if a product entry is sparse

Pricing

Pay-per-result (PPE): from $0.50 per 1,000 products. No subscription. You pay only for what you extract.

Volume	Cost
100 products	~$0.05
1,000 products	~$0.50
10,000 products	~$5.00

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FAQ

Do I need a proxy or API key? No. Open Food Facts is a public database with no authentication required — zero setup, zero friction.

What output formats are available? JSON, CSV, and Excel — downloadable from the Apify dataset UI or via the REST API.

Can I schedule this to run automatically? Yes. Use Apify's scheduler to keep your product database fresh on a cron schedule, with webhook delivery to your pipeline.

What if a barcode is not found or returns an empty result? With skipNotFound: true (default), missing barcodes are silently skipped. With skipNotFound: false, a stub record with parse_confidence=0 and warnings=["product_not_found"] is emitted — useful for auditing your barcode list.

Data source

Open Food Facts — a free, open, collaborative database of food products from around the world. Licensed under ODBL.

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Use with AI agents (MCP)

This actor is available as an MCP tool for Claude, GPT-4, and other AI agents that support the Model Context Protocol:

https://mcp.apify.com/?tools=bovi/openfoodfacts-scraper

Pass a barcode or food keyword and get back full nutritional panels — ideal for AI diet assistants, meal-planning apps, and food-labeling pipelines.

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vs. competitors

	This actor	Typical food scraper
Data source	Official Open Food Facts API	HTML scraping / third-party aggregator
NutriScore + NOVA + Eco-Score	✓	Rarely all three
Barcode lookup (EAN-13/UPC)	✓	Sometimes
parse_confidence	✓	No
Proxy needed	No	Often required
Price	from $0.50/1K	$3–10/1K

Integrations

Built for nutrition-app developers and food-tech teams resolving barcodes to NutriScore, allergens, and macro data — the JSON/dataset output drops into the tools you already run, no glue code:

• n8n / Make / Zapier — trigger a run or pipe every new dataset item into 500+ apps (Google Sheets, Airtable, Slack, HubSpot, your database) with no code: n8n, Make, Zapier.
• Webhooks — fire your own endpoint the moment a run finishes, to push results straight into your pipeline (docs).
• MCP server — expose this actor as a tool to Claude, Cursor, or any MCP client so an AI agent can pull this data mid-conversation (guide).
• API & SDKs — fetch the dataset as JSON, CSV, or Excel through the Apify REST API or the Python / JS SDKs.

See all Apify integrations.

Usage statistics

This Actor creates a small, content-free summary at the end of each run. It is used only to monitor reliability and improve this Actor. A copy is saved as USAGE_STATS in your own Apify key-value store, so you can see the exact record created for your run.

Set disableUsageStats to true in the input to opt out. Nothing is sent then; your USAGE_STATS record only says that statistics were disabled.

Only these fields are recorded:

• schema version, Actor name and build number;
• UTC start and finish hour (not a precise timestamp);
• run duration, number of results and time to the first result, each as a coarse range;
• whether the result was empty, the end status, and an error type from a fixed list;
• memory setting and counts of charged events;
• names of the input fields you set, never their values;
• the selected option for input fields that offer a fixed list of choices (for example a sort order).

We do not collect input text, search terms, URLs, domains, usernames, email addresses, names, proxy credentials, tokens, scraped records, output items, raw error messages, stack traces, or hashes of any of those values. Records are kept for no longer than 13 months, used only as aggregated operational statistics, and never sold or shared.

Additional fields (Phase 2)

This Actor also records your Apify user ID, whether Apify marks the account as paying, the size range of list inputs, the selected country when the input offers a fixed list of countries, and one category from a fixed Actor taxonomy. We use these fields only for aggregate reliability, repeat-use and cross-Actor analysis; reports suppress any cell with fewer than five distinct users.

The same disableUsageStats: true input flag turns these fields off too. The user ID is removed after 13 months; we do not export, sell, share, or attempt to re-identify this data.

Run-outcome signals (v2)

To learn whether a run did what it was asked to do, the record also holds a few more coarse ranges and yes/no flags. None of them contains content:

• the result limit you asked for (a range, when the input has one) and what share of it was delivered;
• results delivered per input item you listed (a range);
• output quality as ranges: how fully the result fields were filled, the share of rows that look like errors, the share of duplicate rows, and how many different fields appeared. These are counted in memory while results are saved; no result content is kept;
• how the run was started (console, API, schedule, webhook, another Actor);
• how it ended: stopped by you, timed out, reached the requested limit, stopped by the charge limit, and how many times the platform moved the run;
• if this Actor reports it: how many items to process worked or failed (ranges) and one failure reason from a fixed list;
• a short code made from the names of the input fields you set, never their values.

Repeat-run fingerprint (v2)

When your Apify user ID is recorded (see above), the record also holds an 8-character one-way code made from your input (proxy settings left out) and this Actor's name. It only lets us see that the same account ran the same input again soon after an unsatisfying run; we never see the input itself. It is stored only in the database, never published, and reports use it in aggregate with the same five-user minimum. It is the one exception to the statement above that no hashes are collected, and disableUsageStats: true turns it off.