EAN / GTIN / UPC Barcode Validator & Product Lookup

Paste a list of barcodes and get one clean, flat row per code back:

• Validation: normalises the code (spaces/hyphens removed), checks the GS1 mod-10 check digit and shows the expected digit when it is wrong.
• Type detection: EAN-13, EAN-8, UPC-A, UPC-E (expanded to UPC-A), GTIN-14 (with indicator digit and contained GTIN-13), ISBN-13, ISBN-10 (converted to ISBN-13), ISMN and ISSN barcodes (977, ISSN derived).
• GS1 prefix → country / region from the embedded public GS1 prefix table (e.g. 300-379 France, 400-440 Germany, 500-509 UK, 000-139 GS1 US).
• Restricted / in-store codes (020-029, 040-049, 200-299 variable-weight and store-internal codes, coupons 050-059 / 981-984 / 990-999, refund receipts 980) are flagged.
• Normalised GTIN-13 and GTIN-14 for every valid code, ready for joining with your ERP, PIM or marketplace feeds.
• Open product data from the free Open Food Facts, Open Beauty Facts, Open Pet Food Facts and Open Products Facts databases: product name, brand, categories, quantity, front image URL, Nutri-Score, NOVA group, Green-Score/Eco-Score, labels, packaging, stores, allergens, countries sold and an optional ingredient list.

No API key, no login, no proxies. Runs in seconds.

Who it is for

• E-commerce and marketplace sellers cleaning product feeds before uploading to Amazon, Google Merchant Center, bol.com or Shopify (wrong check digits are the #1 cause of rejected listings).
• Data teams and PIM/ERP owners normalising mixed UPC/EAN/GTIN-14 columns to one GTIN-14 key.
• Food, nutrition and health apps enriching barcodes with names, images and Nutri-Score.
• AI agents that need a reliable "what is this barcode?" tool via MCP.

Why this actor

• Validation, type detection, GS1 country and product lookup in one row, not four tools.
• Handles the awkward cases others skip: UPC-E expansion, ISBN-10 to ISBN-13, GTIN-14 indicator digits, 12-digit vs 13-digit UPC storage in Open Food Facts.
• Invalid codes are free. You only pay for valid codes.
• Flat, consistent JSON (every row has the same keys) that drops straight into spreadsheets, databases and LLM prompts.
• Polite to the open databases: descriptive User-Agent, low concurrency, retries with back-off, and per-run caching.

Input

{
  "barcodes": ["3017620422003", "5449000000996", "737628064502", "9780141036144", "3017620422004"],
  "lookupProducts": true,
  "databases": ["openfoodfacts", "openbeautyfacts", "openproductsfacts"],
  "language": "en",
  "includeIngredients": false
}

Field	Description
barcodes	Codes to check. Spaces and hyphens are ignored; several codes per line separated by commas also work.
lookupProducts	Turn off for pure offline validation (fastest).
databases	Which Open *Facts databases to search, in order.
language	Preferred language for product names (falls back to the main language).
includeIngredients	Add the ingredients text for food products.
lookupRestrictedCodes	Also look up in-store / restricted prefixes (off by default).
deduplicate	Process identical codes once (default on).

Output

One row per input code, in input order. Real example from a test run (Nutella, shortened):

{
  "position": 1,
  "input": "3017620422003",
  "status": "found",
  "valid": true,
  "type": "EAN-13",
  "found": true,
  "checkDigit": "3",
  "expectedCheckDigit": "3",
  "normalizedGtin13": "3017620422003",
  "normalizedGtin14": "03017620422003",
  "gs1Prefix": "301",
  "gs1PrefixCountry": "France & Monaco",
  "prefixKind": "gs1",
  "isRestricted": false,
  "isbn13": null,
  "productName": "Nutella",
  "brand": "Nutella, Ferrero",
  "quantity": "400 g e",
  "imageUrl": "https://images.openfoodfacts.org/images/products/301/762/042/2003/front_en.879.400.jpg",
  "novaGroup": 3,
  "ecoscoreGrade": "F",
  "genericName": "Hazelnut And Cocoa Spread",
  "countriesSold": "Belgium, France, Germany, Luxembourg",
  "labels": "Vegetarian, No gluten, Triman",
  "allergens": "milk, nuts, soybeans",
  "productUrl": "https://world.openfoodfacts.org/product/3017620422003",
  "source": "Open Food Facts"
}

Other rows from the same run:

input	status	type	GS1 prefix country	product	Nutri-Score
5449000000996	found	EAN-13	Belgium & Luxembourg	Coca-Cola, 330 ml	E
737628064502	found	UPC-A	GS1 US (USA & Canada)	Thai Kitchen Thai peanut noodle kit, 155 g	D
9780141036144	not_found	ISBN-13 (isbn10 0141036141)	Bookland (ISBN)	–	–
3017620422004	invalid (expectedCheckDigit 3)	EAN-13	–	–	–

status is one of found, not_found, valid (lookup off), valid_not_looked_up (restricted code), invalid, lookup_error.

Note: the GS1 prefix shows which national GS1 organisation issued the company prefix. It is a strong hint, but not a guarantee of the country of manufacture.

Pricing

Pay per event: $0.0002 per valid barcode ($0.20 per 1,000). Invalid codes and lookup errors are free. A 10,000-code feed check costs about $2.

Use via API, n8n, Make or MCP

API (sync, returns the rows directly):

curl -X POST "https://api.apify.com/v2/acts/fast_data_asap~ean-gtin-lookup/run-sync-get-dataset-items?token=YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"barcodes": ["3017620422003", "737628064502"]}'

Python:

from apify_client import ApifyClient
client = ApifyClient("YOUR_TOKEN")
run = client.actor("fast_data_asap/ean-gtin-lookup").call(run_input={"barcodes": ["3017620422003"]})
for row in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(row["valid"], row["type"], row["gs1PrefixCountry"], row["productName"])

n8n / Make / Zapier: use the Apify node, action "Run actor and get dataset items", actor fast_data_asap/ean-gtin-lookup.

MCP (Claude, Cursor, other AI agents): add https://mcp.apify.com?tools=fast_data_asap/ean-gtin-lookup as an MCP server and ask "check these barcodes and tell me what the products are".

Data sources and limits

• Product data comes from the open, community-maintained Open Food Facts family of databases (ODbL licence). Coverage is excellent for food and drinks in Europe and good in North America; non-food coverage is smaller. Codes not in these databases are still fully validated and returned with found: false.
• Books (ISBN) are detected and converted, but usually not present in the Open *Facts databases.
• No personal data is processed.