"iFood" matching MCP servers:

MCP server connecting AI models to Swiss Federal Food Safety and Veterinary Office open data, enabling queries about food recalls, animal disease surveillance, food control results, and more.

A production-grade semantic search server for food recipes — built for AI agents using the Model Context Protocol (MCP). Search across 50,000+ recipes with hybrid dense + sparse retrieval and cross-encoder reranking.

Provides tools for UK FSA and EU food safety compliance, including business classification, HACCP auditing, allergen labeling checks, traceability, and recall procedures.

Enables AI agents to search the USDA's FoodData Central database and retrieve detailed nutritional information and ingredient lists. It supports comprehensive food data access through keyword searches and structured queries for specific food items.

Provides 42+ specialized tools for nutrition analysis integrating Canada's Food Guide recipes with Health Canada's official databases (CNF, DRI, EER) for recipe discovery, macro calculations, energy requirements, and dietary adequacy assessments.

Provides access to Hong Kong food data, including wholesale food prices, through a FastMCP interface.

Query UK food hygiene ratings via MCP. Enables searching establishments by name, location, or rating.

Provides tools for nutrition data retrieval, meal planning, and dietary analysis using USDA and Edamam APIs, enabling AI-driven dietary insights.

Provides comprehensive food hierarchy and nutrition data through structured tools that enable searching foods, browsing categories, and retrieving detailed nutritional information from a MongoDB Atlas database.

Enables menu browsing, recommendation requests, and shopping cart management through a Model Context Protocol interface. Users can interact with food order services to query items and handle order additions or removals via natural language.

Provides AI assistants with real-time access to nutrition data from USDA FoodData Central and FatSecret, enabling accurate answers with citations for nutrition queries.

Enables LLMs to search for food products and retrieve detailed nutritional information from the Open Food Facts database using product names or barcodes.

An MCP server that integrates with Google Places API to enable AI clients to search for restaurants and get food recommendations based on location and preferences.

Query food inspection grades and violations for Charlotte/Mecklenburg County, NC, with tools for searching establishments, getting details, finding nearby, and score distributions.

Enables users to search restaurants, view menus, place orders, and check order status via a local MCP server using Firestore.

Enables agents to log and edit meals, query a food journal, and retrieve calorie/macro/quality KPIs with server-side nutritional grading, plus manage staples and targets.