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AIDataNordic

food-recipe-mcp

by AIDataNordic

Food Recipe MCP

Semantische Suche über 50.000+ Kochrezepte – entwickelt für KI-Agenten und LLMs. Zweistufige hybride Suche (dicht + spärlich BM25, fusioniert via RRF) mit Cross-Encoder-Reranking. Unterstützt natürlichsprachliche Anfragen auf Norwegisch und Englisch.

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


Verbinden

Füge dies zu deiner MCP-Client-Konfiguration hinzu:

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

Oder mit Claude Code:

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

Related MCP server: Food MCP Server

Schnelltest

Probiere die Live-Demo in deinem Browser aus:
https://recipes.aidatanorge.no/

Keine Installation oder Konfiguration erforderlich.


MCP-Tools

search_recipes

Semantische Suche über 50.000+ Rezepte von Food.com mit hybrider Suche und 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

Beispielanfragen:

  • "Swedish meatballs with gravy"

  • "healthy high-protein chicken bowl"

  • "easy chocolate cake for beginners"

  • "traditional Norwegian kjøttkaker"

  • "hurtig pasta med kylling"

Such-Pipeline: Dichte Einbettung (intfloat/e5-large-v2, 1024d) + spärliches BM25, fusioniert via Reciprocal Rank Fusion (RRF), neu gerankt durch mmarco-mMiniLMv2-L12-H384-v1.

ping

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

Daten

  • Quelle: Food.com (~50.000 Rezepte)

  • Abdeckung: Große Auswahl an Küchen, Mahlzeitenarten und Kochstilen

  • Nährwertdaten: Kalorien, Fett, Protein, Kohlenhydrate, Natrium, Ballaststoffe, Zucker pro Portion

  • Bewertungen: Nutzerbewertung + Anzahl der Bewertungen pro Rezept

  • Sprachen: Englisch und Norwegisch werden nativ in Anfragen unterstützt


Architektur

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

Technischer Stack

  • Embeddings: intfloat/e5-large-v2 (1024d dicht) + Qdrant/bm25 (spärlich)

  • Reranker: cross-encoder/mmarco-mMiniLMv2-L12-H384-v1

  • Vektor-DB: Qdrant (selbst gehostet)

  • Server: FastMCP 3.2 über HTTP

  • Infrastruktur: Ubuntu Server 24 LTS, Cloudflare Tunnel


Lizenz

MIT

Install Server
A
license - permissive license
A
quality
D
maintenance

Maintenance

Maintainers
Response time
Release cycle
1Releases (12mo)
Commit activity

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