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food-recipe-mcp

food-recipe-mcp

Remote
github.com/AIDataNordicGames & Entertainment1Updated 26w ago
Repository

About food-recipe-mcp

food-recipe-mcp is a semantic recipe search MCP server for AI agents and LLMs, covering more than 50,000 Food.com recipes. It combines dense and sparse retrieval, rank fusion, and cross-encoder reranking, with queries supported in English and Norwegian.

Key features

  1. 01Search over 50,000+ recipes
  2. 02Hybrid dense and BM25 retrieval
  3. 03RRF fusion and cross-encoder reranking
  4. 04Filter by diet, time, and difficulty
  5. 05English and Norwegian queries
  6. 06Nutrition and rating data in results

Use cases

  1. 01Find dinner recipes with natural-language queries
  2. 02Filter recipes for dietary restrictions
  3. 03Choose recipes by cooking time and difficulty
  4. 04Search for local dishes in Norwegian

MCP support

The server provides an MCP interface over streamable HTTP, exposing recipe search and ping tools to MCP clients.

Configuration

Remote servers need no local install. Pick your client, then copy the config or install in one click.

Endpointhttps://recipes.aidatanorge.no/mcp
Copy install command
Claude CodeTerminal
Cursor.cursor/mcp.json
VS Code.vscode/mcp.json
Claude Desktopclaude_desktop_config.json
Windsurf~/.codeium/windsurf/mcp_config.json

Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.

Tools

2
ParameterTypeRequiredDescription
namestringNoArbitrary label included in the response, e.g. 'healthcheck'

Details

From the project 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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