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Food Recipe MCP Server

Developer ToolsUse Caution0.6MCP RegistryRemote
Free

Server data from the Official MCP Registry

Semantic search across 50,000+ food recipes with hybrid retrieval and reranking.

About

Semantic search across 50,000+ food recipes with hybrid retrieval and reranking.

Remote endpoints: streamable-http: https://recipes.aidatanorge.no/mcp

Security Report

0.6
Use Caution0.6Critical Risk

Valid MCP server (0 strong, 4 medium validity signals). 8 known CVEs in dependencies (3 critical, 3 high severity) Imported from the Official MCP Registry. Trust signals: trusted author (2/3 approved).

Endpoint verified · Open access · 8 issues found

Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.

Permissions Required

This plugin requests these system permissions. Most are normal for its category.

HTTP Network Access

Connects to external APIs or services over the internet.

Unverified package source

We couldn't verify that the installable package matches the reviewed source code. Proceed with caution.

How to Connect

Remote Plugin

No local installation needed. Your AI client connects to the remote endpoint directly.

Add this to your MCP configuration to connect:

{
  "mcpServers": {
    "io-github-aidatanordic-food-recipe-mcp": {
      "url": "https://recipes.aidatanorge.no/mcp"
    }
  }
}

Documentation

View on GitHub

From the project's GitHub README.

Food Recipe MCP

Semantic search over 50,000+ food recipes — built for AI agents and LLMs. Two-stage hybrid retrieval (dense + sparse BM25, fused via RRF) with cross-encoder reranking. Supports natural language queries in Norwegian and English.

Live endpoint: https://recipes.aidatanorge.no/mcp
Transport: streamable-http
Demo: https://recipes.aidatanorge.no/


Connect

Add to your MCP client config:

{
  "mcpServers": {
    "food-recipe": {
      "type": "streamable-http",
      "url": "https://recipes.aidatanorge.no/mcp"
    }
  }
}

Or with Claude Code:

claude mcp add --transport http food-recipe https://recipes.aidatanorge.no/mcp

Quick Test

Try the live demo in your browser:
https://recipes.aidatanorge.no/

No installation or configuration needed.


MCP Tools

search_recipes

Semantic search over 50,000+ recipes from Food.com with hybrid retrieval and reranking.

search_recipes(
    query="quick Italian pasta for weeknight dinner",
    diet="vegetarian",      # vegetarian | vegan | gluten-free | dairy-free | low-carb | keto | paleo
    max_minutes=30,         # maximum total cooking time in minutes
    difficulty="easy",      # easy | medium | hard
    limit=5                 # default 5, max 20
)
# Returns: rerank_score, rrf_score, title, description, total_time, difficulty,
#          diet, main_ingredient, servings, ingredients, instructions, nutrition,
#          rating, rating_count, source, recipe_id

Query examples:

  • "Swedish meatballs with gravy"
  • "healthy high-protein chicken bowl"
  • "easy chocolate cake for beginners"
  • "traditional Norwegian kjøttkaker"
  • "hurtig pasta med kylling"

Search pipeline: Dense embedding (intfloat/e5-large-v2, 1024d) + sparse BM25, fused via Reciprocal Rank Fusion (RRF), reranked by mmarco-mMiniLMv2-L12-H384-v1.

ping

ping(name="world")
# Returns: "Hello world! Recipe MCP server is running."

Data

  • Source: Food.com (~50,000 recipes)
  • Coverage: Wide range of cuisines, meal types, and cooking styles
  • Nutritional data: calories, fat, protein, carbohydrates, sodium, fiber, sugar per serving
  • Ratings: user rating + rating count per recipe
  • Languages: English and Norwegian supported natively in queries

Architecture

Food.com recipes → Python ingest → Qdrant (recipe_data_v2 collection)
                                         ↓
                              Hybrid search (dense e5-large-v2 + sparse BM25)
                                         ↓
                              RRF fusion + cross-encoder reranking
                                         ↓
                              FastMCP 3.2 → MCP clients / AI agents

Technical Stack

  • Embeddings: intfloat/e5-large-v2 (1024d dense) + Qdrant/bm25 (sparse)
  • Reranker: cross-encoder/mmarco-mMiniLMv2-L12-H384-v1
  • Vector DB: Qdrant (self-hosted)
  • Server: FastMCP 3.2 over HTTP
  • Infrastructure: Ubuntu Server 24 LTS, Cloudflare Tunnel

License

MIT

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