retailopenfoodfacts/product-databasefoodnutritioningredientsallergensmultilingualopen-dataodbltabularragcrowdsourced

Open Food Facts Product Database

Free

Open dataset

Sample structure: 78.2 / 100

3 download links issued

Seller: DataBazaar

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Source, license and coverage

Supplier documentation. These claims are separate from the automated sample score. A listing edit date is not a data freshness date.

License: agpl-3.0,odbl
Source / creator: huggingface: openfoodfacts/product-database
Collection method: auto_imported_huggingface_federated
Coverage start: Not documented
Coverage end: Not documented
Data last updated: Not documented
Update schedule: Not documented

Source documentation ↗

Sample structure score: 78.2 / 100

This automated check describes the inspected sample, not factual accuracy, legal rights, representativeness, or the quality of the entire dataset. It is not a customer rating.

Assessed 10 sample records (JSON) on 2026-10-09. All records in the provided sample were checked.

Check	Points	Evidence
Populated cells	28.2 / 50	514 of 910 top-level cells contain a value. Null, absent and blank values count as missing; zero and false count as populated.
Consistent value types	30 / 30	514 of 514 populated cells match their column's most common observed type. Types are inferred, not checked against real-world truth.
Consistent record shape	20 / 20	10 of 10 records have the expected fields. CSV/TSV use the header width; JSON uses the union of observed keys.

Field-level findings and improvements

Check missing cells and mixed types below. Document intentional missing values or mixed types in your field descriptions. Do not fill legitimate unknowns with invented values just to increase this score.

Field	Missing cells	Most common type	Other populated types
additives_n	8 / 10	number	0 / 2
additives_tags	0 / 10	object	0 / 10
allergens_tags	0 / 10	object	0 / 10
brands_tags	0 / 10	object	0 / 10
brands	5 / 10	string	0 / 5
categories	8 / 10	string	0 / 2
categories_tags	4 / 10	object	0 / 6
checkers_tags	0 / 10	object	0 / 10
cities_tags	4 / 10	object	0 / 6
code	0 / 10	string	0 / 10
complete	0 / 10	number	0 / 10
completeness	8 / 10	number	0 / 2
correctors_tags	0 / 10	object	0 / 10
countries_tags	0 / 10	object	0 / 10
created_t	0 / 10	number	0 / 10
creator	0 / 10	string	0 / 10
data_quality_errors_tags	9 / 10	object	0 / 1
data_quality_info_tags	9 / 10	object	0 / 1
data_quality_warnings_tags	9 / 10	object	0 / 1
data_sources_tags	9 / 10	object	0 / 1
editors	9 / 10	object	0 / 1
emb_codes_tags	4 / 10	object	0 / 6
emb_codes	10 / 10	unknown	0 / 0
entry_dates_tags	0 / 10	object	0 / 10
generic_name	0 / 10	object	0 / 10
images	0 / 10	object	0 / 10
informers_tags	0 / 10	object	0 / 10
ingredients_analysis_tags	8 / 10	object	0 / 2
ingredients_from_palm_oil_n	8 / 10	number	0 / 2
ingredients_n	8 / 10	number	0 / 2
ingredients_original_tags	4 / 10	object	0 / 6
ingredients_percent_analysis	4 / 10	number	0 / 6
ingredients_tags	0 / 10	object	0 / 10
ingredients_text	0 / 10	object	0 / 10
ingredients_with_specified_percent_n	9 / 10	number	0 / 1
ingredients_with_unspecified_percent_n	9 / 10	number	0 / 1
ingredients	0 / 10	string	0 / 10
known_ingredients_n	8 / 10	number	0 / 2
labels_tags	4 / 10	object	0 / 6
labels	9 / 10	string	0 / 1
lang	0 / 10	string	0 / 10
languages_tags	0 / 10	object	0 / 10
last_edit_dates_tags	0 / 10	object	0 / 10
last_editor	4 / 10	string	0 / 6
last_image_t	1 / 10	number	0 / 9
last_modified_by	4 / 10	string	0 / 6
last_modified_t	0 / 10	number	0 / 10
last_updated_t	0 / 10	number	0 / 10
link	9 / 10	string	0 / 1
main_countries_tags	9 / 10	object	0 / 1
manufacturing_places_tags	4 / 10	object	0 / 6
manufacturing_places	10 / 10	unknown	0 / 0
max_imgid	0 / 10	number	0 / 10
minerals_tags	1 / 10	object	0 / 9
misc_tags	1 / 10	object	0 / 9
nucleotides_tags	1 / 10	object	0 / 9
nutrient_levels_tags	0 / 10	object	0 / 10
nutrition_data_per	0 / 10	string	0 / 10
obsolete	0 / 10	boolean	0 / 10
origins_tags	4 / 10	object	0 / 6
origins	10 / 10	unknown	0 / 0
owner_fields	10 / 10	unknown	0 / 0
owner	10 / 10	unknown	0 / 0
packagings_complete	10 / 10	unknown	0 / 0
packaging_recycling_tags	9 / 10	object	0 / 1
packaging_shapes_tags	9 / 10	object	0 / 1
packaging_tags	4 / 10	object	0 / 6
packaging_text	0 / 10	object	0 / 10
packaging	8 / 10	string	0 / 2
packagings	9 / 10	object	0 / 1
photographers	10 / 10	unknown	0 / 0
popularity_key	9 / 10	number	0 / 1
popularity_tags	9 / 10	object	0 / 1
product_name	0 / 10	object	0 / 10
product_quantity_unit	9 / 10	string	0 / 1
product_quantity	7 / 10	number	0 / 3
purchase_places_tags	4 / 10	object	0 / 6
quantity	5 / 10	string	0 / 5
rev	0 / 10	number	0 / 10
scans_n	9 / 10	number	0 / 1
serving_quantity	2 / 10	number	0 / 8
serving_size	10 / 10	unknown	0 / 0
states_tags	0 / 10	object	0 / 10
stores_tags	4 / 10	object	0 / 6
stores	10 / 10	unknown	0 / 0
traces_tags	0 / 10	object	0 / 10
unique_scans_n	9 / 10	number	0 / 1
unknown_ingredients_n	4 / 10	number	0 / 6
unknown_nutrients_tags	0 / 10	object	0 / 10
vitamins_tags	1 / 10	object	0 / 9
schema_version	0 / 10	number	0 / 10

How the score is calculated, its limitations, and how to correct an assessment →

About this data

Food products with ingredients, allergens, nutrition facts, and label data contributed by volunteers across 150 countries. Multilingual tabular dataset.

Retrieve with your agent or Python

Create an account and configure DATABAZAAR_API_KEY. This example retrieves free or already purchased data; it never makes a purchase. For a multi-file dataset, choose a file index from the manifest.

Download the Python example

python3 retrieve-dataset.py 75d8e1ff-547e-442e-95f3-d528eeace39b --output dataset.bin

Full supplier documentation

_PII signals: us_phone×61, credit_card_candidate×5 (0.3≤score<0.7) present in the sample. Common in public datasets (papers, logs) but worth knowing before joining with private data._ Original supplier listing: Open Food Facts Product Database 1.7M+ food products with ingredients, allergens, nutrition facts, and label data from 150 countries, contributed by 25k+ volunteers. Multilingual tabular dataset under ODbL/AGPL.

Schema

Name	Type	Description
additives_n	INTEGER
additives_tags	VARCHAR[]
allergens_tags	VARCHAR[]
brands_tags	VARCHAR[]
brands	VARCHAR
categories	VARCHAR
categories_tags	VARCHAR[]
checkers_tags	VARCHAR[]
cities_tags	VARCHAR[]
code	VARCHAR
complete	INTEGER
completeness	FLOAT
correctors_tags	VARCHAR[]
countries_tags	VARCHAR[]
created_t	BIGINT
creator	VARCHAR
data_quality_errors_tags	VARCHAR[]
data_quality_info_tags	VARCHAR[]
data_quality_warnings_tags	VARCHAR[]
data_sources_tags	VARCHAR[]
editors	VARCHAR[]
emb_codes_tags	VARCHAR[]
emb_codes	VARCHAR
entry_dates_tags	VARCHAR[]
generic_name	STRUCT(lang VARCHAR, "text" VARCHAR)[]
images	STRUCT("key" VARCHAR, imgid INTEGER, rev INTEGER, sizes STRUCT("100" STRUCT(h INTEGER, w INTEGER), "200" STRUCT(h INTEGER, w INTEGER), "400" STRUCT(h INTEGER, w INTEGER), "full" STRUCT(h INTEGER, w INTEGER)), uploaded_t BIGINT, uploader VARCHAR)[]
informers_tags	VARCHAR[]
ingredients_analysis_tags	VARCHAR[]
ingredients_from_palm_oil_n	INTEGER
ingredients_n	INTEGER
ingredients_original_tags	VARCHAR[]
ingredients_percent_analysis	INTEGER
ingredients_tags	VARCHAR[]
ingredients_text	STRUCT(lang VARCHAR, "text" VARCHAR)[]
ingredients_with_specified_percent_n	INTEGER
ingredients_with_unspecified_percent_n	INTEGER
ingredients	VARCHAR
known_ingredients_n	INTEGER
labels_tags	VARCHAR[]
labels	VARCHAR
lang	VARCHAR
languages_tags	VARCHAR[]
last_edit_dates_tags	VARCHAR[]
last_editor	VARCHAR
last_image_t	BIGINT
last_modified_by	VARCHAR
last_modified_t	BIGINT
last_updated_t	BIGINT
link	VARCHAR
main_countries_tags	VARCHAR[]
manufacturing_places_tags	VARCHAR[]
manufacturing_places	VARCHAR
max_imgid	INTEGER
minerals_tags	VARCHAR[]
misc_tags	VARCHAR[]
nucleotides_tags	VARCHAR[]
nutrient_levels_tags	VARCHAR[]
nutrition_data_per	VARCHAR
obsolete	BOOLEAN
origins_tags	VARCHAR[]
origins	VARCHAR
owner_fields	STRUCT(field_name VARCHAR, "timestamp" BIGINT)[]
owner	VARCHAR
packagings_complete	BOOLEAN
packaging_recycling_tags	VARCHAR[]
packaging_shapes_tags	VARCHAR[]
packaging_tags	VARCHAR[]
packaging_text	STRUCT(lang VARCHAR, "text" VARCHAR)[]
packaging	VARCHAR
packagings	STRUCT(material VARCHAR, number_of_units BIGINT, quantity_per_unit VARCHAR, quantity_per_unit_unit VARCHAR, quantity_per_unit_value VARCHAR, recycling VARCHAR, shape VARCHAR, weight_measured FLOAT)[]
photographers	VARCHAR[]
popularity_key	BIGINT
popularity_tags	VARCHAR[]
product_name	STRUCT(lang VARCHAR, "text" VARCHAR)[]
product_quantity_unit	VARCHAR
product_quantity	VARCHAR
purchase_places_tags	VARCHAR[]
quantity	VARCHAR
rev	INTEGER
scans_n	INTEGER
serving_quantity	VARCHAR
serving_size	VARCHAR
states_tags	VARCHAR[]
stores_tags	VARCHAR[]
stores	VARCHAR
traces_tags	VARCHAR[]
unique_scans_n	INTEGER
unknown_ingredients_n	INTEGER
unknown_nutrients_tags	VARCHAR[]
vitamins_tags	VARCHAR[]
schema_version	INTEGER

Sample Data

Preview a sample of the data before downloading.

Public sample only. Sign in to retrieve the full dataset, including free datasets.

For AI Agents

Via MCP Server

# 1. Add to your agent's MCP config (claude_desktop_config.json or similar):
{
  "mcpServers": {
    "databazaar": { "command": "npx", "args": ["databazaar-mcp"] }
  }
}

# 2. Your agent can then call:
search_datasets({ query: "Open Food Facts Product Databa" })
// Found: 75d8e1ff-547e-442e-95f3-d528eeace39b
get_download_url({ dataset_id: "75d8e1ff-547e-442e-95f3-d528eeace39b" })  // free — sign in with MCP OAuth first

Via REST API

# Free dataset — sign in or use your account API key:
curl https://api.databazaar.io/datasets/75d8e1ff-547e-442e-95f3-d528eeace39b/download-url -H "Authorization: Bearer $DATABAZAAR_API_KEY"