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Semantic search across 50,000+ food recipes with hybrid retrieval and reranking.
Semantic search across 50,000+ food recipes with hybrid retrieval and reranking.
Remote endpoints: streamable-http: https://recipes.aidatanorge.no/mcp
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
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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"
}
}
}From the project's GitHub README.
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/
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
Try the live demo in your browser:
https://recipes.aidatanorge.no/
No installation or configuration needed.
search_recipesSemantic 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.
pingping(name="world")
# Returns: "Hello world! Recipe MCP server is running."
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
intfloat/e5-large-v2 (1024d dense) + Qdrant/bm25 (sparse)cross-encoder/mmarco-mMiniLMv2-L12-H384-v1MIT
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