retailopenfoodfacts/product-databasefoodnutritioningredientsallergensmultilingualopen-dataodbltabularragcrowdsourced
Open Food Facts Product Database
About this data
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.
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{
"mcpServers": {
"databazaar": { "command": "npx", "args": ["databazaar-mcp"] }
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# 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 — no API key neededVia REST API
# Free dataset — no API key required: curl https://api.databazaar.io/datasets/75d8e1ff-547e-442e-95f3-d528eeace39b/download-url