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  1. Home
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  3. Food Recipe MCP
Food Recipe MCP logo
Health: ActiveRecent health check succeeded.Last checked 9/11/2026, 6:32:31 PM

Food Recipe MCP

User RatingsBe the first to rate and review this MCP server!
View Repository1 GitHub StarsTotal stargazers on GitHub for the source repository (1 stars).Visit Website
recipesfoodsemantic-searchrag

Searches 50,000+ Food.com recipes using semantic retrieval, dietary filters, cooking time, and difficulty.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β€” or use 1-click editor setup below.

Add to CursorAdd to VS Code
Manual Client & Custom JSON ConfigExpand JSON β–Ύ

Client Config & Setup

Remote HTTP
Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "aidatanordic-food-recipe-mcp": {
      "url": "https://recipes.aidatanorge.no/mcp"
    }
  }
}

πŸ’‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Tool Schemas (1) Directory Badge Claim listing AlternativesπŸ› οΈ More in Other Tools and Integrations

Overview

AIDataNordic/Food-Recipe-MCP MCP server exposes recipe search over MCP through a hosted streamable HTTP endpoint. Its search combines dense embeddings and sparse BM25 retrieval, fuses results with reciprocal rank fusion, and applies cross-encoder reranking. Queries can be written in English or Norwegian and filtered by diet, maximum cooking time, and difficulty. Reach for it when an agent needs recipe discovery, meal planning, or recipe details from the Food.com dataset without running local infrastructure.

Use cases

β€’Find recipes from natural-language meal descriptions
β€’Filter meal ideas by diet and cooking time
β€’Suggest dishes by difficulty level
β€’Retrieve ingredients, instructions, and nutrition
β€’Search for English or Norwegian recipes

Key features

β€’Semantic search across approximately 50,000 Food.com recipes
β€’Hybrid dense and BM25 retrieval
β€’Reciprocal rank fusion and cross-encoder reranking
β€’Diet, cooking-time, and difficulty filters
β€’English and Norwegian query support
β€’Recipe nutrition, ratings, and instructions

Capabilities & Tool Schemas (1) ~25 tokensApproximate context cost of this server’s tool schemas (~4 chars/token), before any tool is called. Actual usage depends on your client and model.Self-reported Self-reportedParsed from the repository README, not verified against a live server β€” may be incomplete or out of date.

Inspect callable tools, capabilities, and parameters exposed to AI agents by Food Recipe MCP.

search_recipes

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

How Food Recipe MCP works

What AIDataNordic/Food-Recipe-MCP MCP server does

AIDataNordic/Food-Recipe-MCP MCP server provides MCP clients with search access to approximately 50,000 recipes sourced from Food.com. The main use case is finding recipes from natural-language descriptions rather than relying only on exact keyword matches. Example searches include weeknight pasta, Swedish meatballs, high-protein chicken bowls, and Norwegian dishes such as kjΓΈttkaker.

Search results can include the recipe title, description, preparation and cooking time, difficulty, diet information, main ingredient, servings, ingredients, instructions, nutrition, rating, rating count, source, and recipe ID. The underlying collection covers multiple cuisines, meal types, and cooking styles.

How it works

The hosted service processes each search through a two-stage retrieval pipeline. Dense vector search uses the intfloat/e5-large-v2 embedding model, while sparse retrieval uses BM25. Results from those methods are combined with Reciprocal Rank Fusion and then reordered by a cross-encoder reranker.

This approach supports semantic queries in both English and Norwegian. The search tool accepts an optional diet value, a maximum total cooking time in minutes, a difficulty value, and a result limit. Supported diet filters include vegetarian, vegan, gluten-free, dairy-free, low-carb, keto, and paleo. Difficulty can be set to easy, medium, or hard. The result limit defaults to five and can be increased to a maximum of 20.

Setup and configuration

AIDataNordic/Food-Recipe-MCP MCP server is available at https://recipes.aidatanorge.no/mcp using the streamable HTTP transport. Add that URL to an MCP client as a server named food-recipe, or register it with Claude Code using the HTTP transport. The README also provides a browser demo at https://recipes.aidatanorge.no/ for trying the service.

The hosted connection requires no local installation or configuration according to the project instructions. The repository describes the service as running with FastMCP over HTTP, Qdrant for its recipe collection, and a Cloudflare Tunnel for infrastructure access. Those implementation details are relevant if you are evaluating the project architecture, but the documented client connection uses only the remote MCP URL.

Tools and capabilities

The AIDataNordic/Food-Recipe-MCP MCP server exposes these tools:

  • search_recipes: Searches the Food.com recipe collection with hybrid semantic and sparse retrieval, reranking, and optional diet, time, difficulty, and result-count filters.
  • ping: Accepts a name and returns a response confirming that the recipe server is running.

Nutrition fields in returned recipes include calories, fat, protein, carbohydrates, sodium, fiber, and sugar per serving. Ratings include both the user rating and rating count when available.

Limitations and notes

The searchable data comes from Food.com and is described as approximately 50,000 recipes; it is not presented as a general-purpose recipe database beyond that source. Search results expose recipe information and metadata, but the provided material does not describe functions for creating, editing, saving, or rating recipes.

The documented remote endpoint is the supported connection method in the README. No API key, OAuth flow, or other credential configuration is specified. Although the project uses local components such as Qdrant and embedding models in its architecture, the material does not provide a verified command for running a local copy of AIDataNordic/Food-Recipe-MCP MCP server.

Read the full README β†’View source on GitHub β†’

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Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks β€” not a rating.

GitHub stars
1
Stargazers on the source repository.
Last commit
1mo ago
Most recent push to the default branch.
Tools exposed
1
Callable tools this server registers over MCP.
Directory activity
3 views
Config copies, upvotes, and views on AllMCPs.

Reviews

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Frequently Asked Questions about Food Recipe MCP

Use the hosted streamable HTTP endpoint at https://recipes.aidatanorge.no/mcp in your MCP client. The README says no local installation or configuration is needed.

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Technical Specs & Signals

CategoryπŸ› οΈOther Tools and Integrations
PricingFree
More technical detailsExpand β–Ύ
TransportSSE (Remote)
AuthNo auth required
LicenseMIT
ClientsClaude Desktop
Last updatedSep 7, 2026
Views3
Unique ViewsTotal visits recorded for this listing page on AllMCPs.
Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars1
GitHub Star CountTotal stargazers on GitHub representing community popularity (1 stars).
Last commit1mo ago
Last Repository CommitThe most recent commit or push recorded for this server's GitHub repository.Last commit on Jul 14, 2026
53Quality signal: Good Β· 53/100How this signal is calculated β–Ύ
Server availabilityNot measured

Not scored for repo-hosted servers β€” we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20
Documentation & tools27/30
Adoption & activity3/15
Community engagement0/10

A guidance signal from public completeness & health data β€” not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

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