io.github.cyanheads/openfoodfacts-mcp-server

Resolve a human term to the canonical Open Food Facts tag ID that off_search_products filters on. Covers categories, labels/certifications, allergens, additives, countries, ingredients, NOVA groups, and Nutri-Score grades. Pass a search term to resolve against the Open Food Facts vocabulary, which holds tens of thousands of tags; omitting it returns only a small reference list for each facet except NOVA groups and Nutri-Score grades, which are complete, and ingredients, which has no reference list and returns nothing. Most tag IDs use the "en:" prefix (e.g. "en:organic", "en:no-gluten", "en:crustaceans"); NOVA groups return bare digits "1"-"4" and Nutri-Score grades bare letters "a"-"e". Pass the id through to off_search_products exactly as returned. Category tags are frequently plural ("kombucha" resolves to "en:kombuchas") and ingredient tags singular ("oat" resolves to "en:oat", "oats" to nothing), so use the returned id rather than constructing one.

Side-by-side nutrition and scoring comparison for 2–10 products per call by barcode; a repeated barcode is compared once, so two identical barcodes yield one row, and barcodes past the 10th distinct one are listed in unprocessed rather than fetched. Returns a normalized table of energy (kcal), fat, saturated fat, carbohydrates, sugars, salt, protein, and fiber per 100 g, or per 100 ml for liquids, plus Nutri-Score, NOVA group, and Green-Score. Open Food Facts returns one preparation state per read, so figures for the prepared product arrive in a prepared object on the row, with the same columns and basis, and never fill an as-sold field; a row whose read returned only prepared figures gets one more product read, of the as-sold set its record stores, once the read of every barcode has settled, with stored_as_sold saying how it went. Designed for "which of these cereals is healthiest?" or "compare these pasta brands" workflows. Missing nutrition data for any product is preserved as absent — comparisons are not imputed. A batch is not all-or-nothing: barcodes that resolve are returned even when others fail, with confirmed-missing barcodes listed in not_found and failed fetches listed separately in failed. Scores carry regional formula caveats. Data under ODbL 1.0 — cite Open Food Facts in downstream use.

Fetch a packaged food product by barcode (4–40 digits: EAN-13, EAN-8, UPC, and the shorter and longer codes Open Food Facts also holds) from Open Food Facts. Returns the product name and generic name, brand, quantity, ingredients (raw text and parsed list), declared allergens, trace allergens the label warns about, additives, the product-level vegan/vegetarian/palm-oil analysis, computed scores (Nutri-Score a–e, NOVA 1–4, Green-Score), the low/moderate/high levels of fat, saturated fat, sugars, and salt Open Food Facts computes, nutrition per serving and per 100 g, or per 100 ml for liquids, categories, labels, packaging, origins, countries of sale, image URL, and data completeness. Open Food Facts is a crowd-sourced database — a missing field means "not yet entered by contributors," not that the attribute is absent from the actual product. Nutrition is the exception: Open Food Facts returns one preparation state per read, so a read of prepared figures (_prepared keys under nutriments) omits as-sold figures the record can still hold; when that happens, one more product read fetches the as-sold set the record stores into the as-sold fields, and nutriments.stored_as_sold says whether it was read, the record stores none, or it could not be read. Computed scores carry regional formula caveats and are indicators, not absolute rankings. Data is under ODbL 1.0 — cite Open Food Facts in downstream use.

Search Open Food Facts by full-text query, structured tag filters, or both at once. Returns a summary list with barcodes, product names, brands, Nutri-Score, NOVA group, Green-Score, and categories — enough for triage and selection, not full label data. Use off_get_product on the returned barcodes for complete details. A text query and tag filters combine: every word of the query must match the product name, generic name, categories, labels, or brand, and every filter provided must hold (e.g. query "dark chocolate" with labels_tag "en:organic" and countries_tag "en:france" returns organic chocolate sold in France); numeric nutrient_filters express thresholds per 100 g, or per 100 ml for liquids, such as sugars below 8 g, and combine the same way, and each row then carries the indexed values the thresholds were checked against; ingredients_tag takes canonical ingredient IDs (e.g. "en:inulin") that must all appear among the ingredients Open Food Facts parsed from the label, and combines the same way; additives_tag is the one exception, filtering only on searches carrying none of query, nutrient_filters, or ingredients_tag. nutrition_grade, nova_group, and ecoscore_grade (Green-Score) each take one grade or an array matching any of them. Tag filter values are canonical tag IDs (e.g. "en:organic", "en:no-gluten") — use off_browse_taxonomy to resolve human terms to tag IDs. A case variant, synonym, or singular of a tag is resolved to its canonical ID where Open Food Facts recognizes it; anything else is matched exactly. exclude_allergens and exclude_traces drop products that declare an allergen or a "may contain" trace, but a product with no allergen or trace data entered passes them, so confirm a candidate with off_get_product before relying on it. At least one search parameter is required. The two paths read different indexes: a search carrying query, nutrient_filters, or ingredients_tag is answered by the text index, a snapshot that lags the live database, while a tag-only search reads the live database and is current, or, where this server keeps a local copy of the Open Food Facts export, can be served from that copy, which source and mirror_as_of then report and whose default order and popularity_key or unique_scans_n sort follow the values stored with each record, so they can differ from a live search, which ranks by its current scan counts — so a recently contributed product can be missing from a text search and present in the same search without query. Data is crowd-sourced; result count reflects contributed products, not all products in the market. Data under ODbL 1.0 — cite Open Food Facts in downstream use.