openfoodfacts-mcp-server

<div align="center"> <h1>@cyanheads/openfoodfacts-mcp-server</h1> <p><b>Look up food products by barcode, search by ingredient or nutrition filter, compare products side-by-side, and browse the canonical tag vocabulary via MCP. STDIO or Streamable HTTP.</b> <div>4 Tools</div> </p> </div>

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Public Hosted Server: https://openfoodfacts.caseyjhand.com/mcp

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Tools

Four tools for working with Open Food Facts — a free, crowd-sourced database of 3M+ packaged food products:

| Tool | Description | |:-----|:------------| | off_get_product | Fetch a packaged food product by barcode. Returns name, brand, quantity, ingredients, allergens, additives, Nutri-Score, NOVA group, Green-Score, nutrition per 100g/serving, categories, labels, and data completeness. | | off_search_products | Search by text query and/or structured tag filters (category, brand, label, allergen, additive, Nutri-Score grade, NOVA group, country). Returns summary rows with barcodes for follow-up lookups. | | off_compare_products | Side-by-side nutrition and scoring comparison for 2–10 products by barcode. Returns a normalized table of energy, macros, salt, Nutri-Score, NOVA, and Green-Score. | | off_browse_taxonomy | Resolve a human term to the canonical tag ID (categories, labels, allergens, additives, countries, NOVA groups, Nutri-Score grades) that off_search_products filters on, against the live Open Food Facts taxonomy. |

off_get_product

Fetch a packaged food product by barcode (EAN-13 or UPC).

• Accepts 8–14 digit barcodes (EAN-13, EAN-8, UPC-A, UPC-E)
• Returns ingredients (raw text and parsed list with percent estimates, vegan/vegetarian flags), all 14 major allergens as tag IDs, E-number additives, Nutri-Score a–e, NOVA 1–4, Green-Score/Eco-Score, every nutrient Open Food Facts holds per 100g and per serving, the serving size those per-serving figures are measured against, categories/labels/packaging/origins as canonical tag IDs, front image URL, and data completeness score (0–1)
• Optional fields parameter restricts the response to a subset (e.g., scores only, or nutrition only)
• Open Food Facts is crowd-sourced — a missing field means "not yet entered by contributors," not that the attribute is absent from the actual product
• A barcode no contributor has recorded raises the not_found error carrying a recovery hint — it is never returned as an empty result

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off_search_products

Search Open Food Facts by text and/or structured tag filters.

• Full-text search across product names, brands, and ingredients
• Structured filters: categories_tag, brands_tag, labels_tag, allergens_tag, additives_tag, nutrition_grade (a–e), nova_group (1–4), countries_tag
• Text query and tag filters combine — a query with filters returns products that match the text and satisfy every filter (e.g., query: "dark chocolate" + labels_tag: en:organic + countries_tag: en:france)
• All filter values are canonical tag IDs — use off_browse_taxonomy to resolve human terms (e.g., "organic" → en:organic). brands_tag takes a brand slug and matches it exactly; open-ended brand wording belongs in query
• additives_tag filters only on searches with no text query — the text backend does not index additives, so pairing the two is rejected up front rather than returning an empty result set that looks like "no such product"
• Pagination via page (1-based) and page_size (1–50, default 20)
• total is exact on tag-only searches. Text searches stop counting at 10,000 matches, and when that ceiling is hit the response says so with total_is_lower_bound: true and renders the count as 10000+ — add filters for an exact figure
• Searches carrying a text query serve only the first 10,000 results — a deeper page * page_size is rejected up front with the highest reachable page, not sent and retried. Tag-only searches publish no window, but deep pages are refused unpredictably, so narrowing the filters beats paging far in
• Returns summary rows (barcode, name, brand, Nutri-Score, NOVA, categories) — use off_get_product for full label data
• Result counts reflect contributed products, not total products on the market
• Search limited to ~10 requests/min by this server's own client-side budget, kept well inside what Open Food Facts asks of clients

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off_compare_products

Side-by-side nutrition and scoring comparison for 2–10 barcodes.

• Accepts 2–10 barcodes, compared in the order provided
• Returns a normalized comparison table: energy (kcal/100g), fat, saturated fat, sugars, salt, protein, fiber, Nutri-Score, NOVA group, and Green-Score
• Missing nutrition data is preserved as null — comparisons are not imputed or estimated
• not_found list identifies barcodes with no contributor record (partial results are not an error)
• failed list identifies barcodes whose fetch failed, with the per-barcode reason — kept separate from not_found, which claims the opposite. A failed barcode never blocks the rows that resolved

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off_browse_taxonomy

Resolve a human term to the canonical Open Food Facts tag ID before building off_search_products filters.

• Facets: categories, labels, allergens, additives, countries, nova_groups, nutrition_grades
• With a search term, the five open facets resolve against the live Open Food Facts taxonomy — tens of thousands of category tags, not a fixed local list. Matching is case-insensitive substring against tag ID or display name (e.g., "gluten" → en:no-gluten, en:gluten-free)
• Upstream tags are often plural ("kombucha" → en:kombuchas) — pass the returned id through unchanged rather than constructing one
• nova_groups and nutrition_grades are closed vocabularies answered offline and returned complete. Their IDs are bare (1–4, a–e), matching what off_search_products accepts
• Live results are merged behind an in-process sample that also serves offline operation. If Open Food Facts is unreachable or the taxonomy budget is spent, the tool answers from that sample and says so rather than failing — an empty result is never presented as an authoritative "no such tag"
• Omitting search lists only the offline sample. The upstream taxonomy endpoint suggests against a term and cannot enumerate a facet, so an unfiltered call is not a view of the full vocabulary and reports no facet total
• limit controls results returned (1–100, default 20). There is no offset or page input — the upstream endpoint offers no cursor, so narrow the term instead
• Taxonomy lookups carry their own ~10 requests/min client-side budget, separate from the search budget

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Features

Built on @cyanheads/mcp-ts-core:

• Declarative tool definitions — single file per tool, framework handles registration and validation
• Unified error handling — handlers throw, framework catches, classifies, and formats
• Pluggable auth: none, jwt, oauth
• Swappable storage backends: in-memory, filesystem, Supabase, Cloudflare KV/R2/D1
• Structured logging with optional OpenTelemetry tracing
• STDIO and Streamable HTTP transports

Open Food Facts-specific:

• No API key required — the identifying User-Agent header (required by OFF terms) is baked into the service layer
• Token-bucket rate limiting per endpoint class: product reads (~15/min), search (~10/min), taxonomy resolution (~10/min). The product and search defaults are the per-IP ceilings Open Food Facts publishes; lower them on a shared outbound IP. A local refusal says so — it never reports itself as an Open Food Facts rate limit
• Automatic retry (3 attempts, 500ms base) for transient failures only — 5xx, timeouts, and 429 (honoring Retry-After), with HTML error page detection for 503 during high load. A 4xx is never retried; the upstream's own explanation is surfaced instead
• Nutriments normalized from raw hyphenated keys (energy-kcal_100g) to underscore form — the _100g and _serving variants of every nutrient on the record, with the macros as named fields and the rest in an open map that carries each nutrient's own unit (micronutrients are reported in grams, so calcium 0.071 is 71 mg)
• Live tag resolution for off_browse_taxonomy against the Open Food Facts taxonomy, merged behind a small in-process sample that covers offline operation and is authoritative for E-number lookups, which the upstream suggester answers poorly

Agent-friendly output:

• Per-serving nutrition always carries its denominator — serving_size as printed plus the parsed serving_quantity/serving_quantity_unit, and an explicit note when Open Food Facts has recorded none
• Missing fields signal incomplete crowd-sourced data, not product attribute absence — surfaced in descriptions and format output
• Computed scores (Nutri-Score, NOVA, Green-Score) returned as-is with regional caveat notes — not interpreted or normalized to health claims
• not_found list in off_compare_products allows partial batch comparisons without request failure — and a barcode whose fetch failed lands in failed instead, so a transport error is never reported as "no contributor record"
• Every failure carries a declared reason and a recovery hint on both client surfaces — timeouts, upstream outages, upstream rejections, and rate limits each resolve to their own error code and their own next step

Getting started

Public Hosted Instance

A public instance is available at https://openfoodfacts.caseyjhand.com/mcp — no installation required. Point any MCP client at it via Streamable HTTP:

{
  "mcpServers": {
    "openfoodfacts-mcp-server": {
      "type": "streamable-http",
      "url": "https://openfoodfacts.caseyjhand.com/mcp"
    }
  }
}

Self-Hosted / Local

No API key is required. Add the following to your MCP client configuration file.

{
  "mcpServers": {
    "openfoodfacts-mcp-server": {
      "type": "stdio",
      "command": "bunx",
      "args": ["@cyanheads/openfoodfacts-mcp-server@latest"],
      "env": {
        "MCP_TRANSPORT_TYPE": "stdio",
        "MCP_LOG_LEVEL": "info"
      }
    }
  }
}

Or with npx (no Bun required):

{
  "mcpServers": {
    "openfoodfacts-mcp-server": {
      "type": "stdio",
      "command": "npx",
      "args": ["-y", "@cyanheads/openfoodfacts-mcp-server@latest"],
      "env": {
        "MCP_TRANSPORT_TYPE": "stdio",
        "MCP_LOG_LEVEL": "info"
      }
    }
  }
}

Or with Docker:

{
  "mcpServers": {
    "openfoodfacts-mcp-server": {
      "type": "stdio",
      "command": "docker",
      "args": [
        "run", "-i", "--rm",
        "-e", "MCP_TRANSPORT_TYPE=stdio",
        "ghcr.io/cyanheads/openfoodfacts-mcp-server:latest"
      ]
    }
  }
}

For Streamable HTTP, set the transport and start the server:

MCP_TRANSPORT_TYPE=http MCP_HTTP_PORT=3010 bun run start:http
# Server listens at http://localhost:3010/mcp

Prerequisites

• Bun v1.3.0 or higher (or Node.js v24+).
• No API key needed. The server sends an identifying User-Agent to comply with Open Food Facts' terms of service — this is baked in and requires no configuration.

Installation

1. Clone the repository:

git clone https://github.com/cyanheads/openfoodfacts-mcp-server.git

1. Navigate into the directory:

cd openfoodfacts-mcp-server

1. Install dependencies:

bun install

1. Configure environment:

cp .env.example .env
# edit .env if you need to override rate limits or the base URL

Configuration

All configuration is validated at startup via Zod schemas in src/config/server-config.ts.

| Variable | Description | Default | |:---------|:------------|:--------| | OFF_BASE_URL | Open Food Facts API base URL. Override for local testing against a mock server. | https://world.openfoodfacts.org | | OFF_RATE_LIMIT_PRODUCT | Product read rate limit (requests/min). Matches the 15 req/min/IP Open Food Facts documents for product reads. | 15 | | OFF_RATE_LIMIT_SEARCH | Search rate limit (requests/min). | 10 | | OFF_RATE_LIMIT_TAXONOMY | Taxonomy resolution rate limit (requests/min). A spent budget falls back to the offline sample rather than failing. | 10 | | MCP_TRANSPORT_TYPE | Transport: stdio or http. | stdio | | MCP_HTTP_PORT | HTTP server port. | 3010 | | MCP_AUTH_MODE | Auth mode: none, jwt, or oauth. | none | | MCP_LOG_LEVEL | Log level (debug, info, warning, error). | info | | LOGS_DIR | Log file directory (Node.js only). | <project-root>/logs | | OTEL_ENABLED | Enable OpenTelemetry instrumentation. | false |

See .env.example for the full list of optional overrides.

Attribution: Open Food Facts data is released under the Open Database License (ODbL) 1.0. Downstream use must cite Open Food Facts.

Running the server

Local development

• Build and run:

  # One-time build
  bun run rebuild

  # Run the built server
  bun run start:stdio
  # or
  bun run start:http

• Run checks and tests:

  bun run devcheck   # Lint, format, typecheck, security
  bun run test       # Vitest test suite
  bun run lint:mcp   # Validate MCP definitions against spec

Docker

docker build -t openfoodfacts-mcp-server .
docker run --rm -p 3010:3010 openfoodfacts-mcp-server

The Dockerfile defaults to HTTP transport, stateless session mode, and logs to /var/log/openfoodfacts-mcp-server. OpenTelemetry peer dependencies are installed by default — build with --build-arg OTEL_ENABLED=false to omit them.

Project structure

| Directory | Purpose | |:----------|:--------| | src/index.ts | createApp() entry point — registers tools and inits services. | | src/config | Server-specific environment variable parsing and validation with Zod. | | src/mcp-server/tools | Tool definitions (*.tool.ts). | | src/services/openfoodfacts | Open Food Facts API client — HTTP, rate limiting, retry, field normalization. | | src/services/taxonomy | Tag vocabulary service for off_browse_taxonomy — live resolution, offline sample, merge and fallback policy. | | tests/ | Unit and integration tests mirroring src/. |

Development guide

See CLAUDE.md for development guidelines and architectural rules. The short version:

• Handlers throw, framework catches — no try/catch in tool logic
• Use ctx.log for request-scoped logging, ctx.state for tenant-scoped storage
• Register new tools via the barrel in src/mcp-server/tools/definitions/index.ts
• Wrap external API calls: validate raw → normalize to domain type → return output schema; never fabricate missing fields

Contributing

Issues and pull requests are welcome. Run checks and tests before submitting:

bun run devcheck
bun run test

License

Apache-2.0 — see LICENSE for details.