Recipe Research MCP Server

Recipe Research MCP Server

Enables recipe search, storage, and meal planning using TheMealDB API. Provides comprehensive recipe discovery, automatic recipe collection management, and custom meal plan creation with detailed cooking instructions and ingredients.

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README

Recipe Research MCP Server

A comprehensive Model Context Protocol (MCP) server that provides recipe search, storage, and meal planning functionality using TheMealDB API. Built with FastMCP and designed for both local development and remote deployment.

🚀 Features

🔍 Recipe Search & Discovery

  • Search recipes by dish name or cuisine
  • Find recipes starting with specific letters
  • Get random recipe suggestions
  • Detailed recipe information with ingredients, instructions, and metadata

📊 Recipe Management

  • Automatic recipe storage and indexing
  • Fast recipe lookup system
  • Recipe collection organization by cuisine/dish type
  • Cross-platform file handling with proper sanitization

🍽️ Meal Planning

  • Create custom meal plans from selected recipes
  • Save and manage multiple meal plans
  • Recipe collection statistics and insights

🎯 MCP Integration

  • Tools: Interactive recipe search and meal planning functions
  • Resources: Read-only access to recipe collections and statistics
  • Prompts: Pre-defined templates for cooking education and analysis

📋 Requirements

  • Python: 3.12 or higher
  • Package Manager: UV (recommended)
  • Dependencies:
    • mcp[cli]>=1.15.0
    • httpx>=0.28.1
    • aiofiles>=24.1.0

🛠️ Installation

Using UV (Recommended)

# Clone the repository
git clone https://github.com/suraj-yadav-aiml/recipe-mcp.git
cd recipe-mcp

# Create and activate virtual environment
uv venv
# On Windows
.venv\Scripts\activate
# On macOS/Linux
source .venv/bin/activate

# Install dependencies
uv sync

# Test the MCP Server
mcp dev recipe_server.py

Using pip

# Create virtual environment
python -m venv .venv

# Activate virtual environment
# On Windows
.venv\Scripts\activate
# On macOS/Linux
source .venv/bin/activate

# Install dependencies
pip install -r requirements.txt

# Test the MCP Server
mcp dev recipe_server.py

🚀 Usage

Local Development (STDIO Transport)

if __name__ == "__main__":
    mcp.run(transport="stdio") 

Remote Deployment (HTTP Transport)


if __name__ == "__main__":
    mcp.run(transport="streamable-http") 

MCP Client Configuration

Option 1: Remote MCP Server (Recommended)

Add to Claude Desktop as Custom Connector:

  1. Open Claude Desktop and go to Settings
  2. Navigate to Connectors section
  3. Click Add Custom Connector
  4. Configure with the following details:
    • Name: Recipe Research MCP
    • URL: https://recipe-mcp.onrender.com/mcp

This connects to our hosted Recipe MCP server without any local setup required.

Option 2: Local MCP Server

Add to your MCP client configuration file:

{
  "recipe_research": {
    "command": "uv",
    "args": [
      "run",
      "--with",
      "mcp[cli]",
      "httpx",
      "aiofiles",
      "mcp",
      "run",
      "path/to/recipe_server.py"
    ],
    "cwd": "path/to/project",
    "env": {
      "PYTHONPATH": "path/to/project"
    }
  }
}

Or for Windows:

{
  "recipe_research": {
    "command": "C:\\Users\\Admin\\.local\\bin\\uv.EXE",
    "args": [
      "--directory",
      "path/to/project",
      "run",
      "path/to/project/recipe_server.py"
    ]
  }
}

🔧 API Reference

Tools

search_recipes(dish_name: str, max_results: int = 5)

Search for recipes by dish name using TheMealDB API.

Example:

# Search for pasta recipes
results = await search_recipes("pasta", max_results=10)

get_recipe_details(recipe_id: str)

Get detailed information about a specific recipe by ID.

Example:

# Get details for recipe ID 52771
details = await get_recipe_details("52771")

create_meal_plan(recipe_ids: List[str], plan_name: str = "My Meal Plan")

Create a meal plan from selected recipe IDs.

Example:

# Create a meal plan
plan = await create_meal_plan(
    ["52771", "52772", "52773"],
    "Italian Week"
)

search_by_first_letter(letter: str, max_results: int = 5)

Search for recipes that start with a specific letter.

Example:

# Find recipes starting with 'A'
results = await search_by_first_letter("A")

get_random_recipe()

Get a random recipe from TheMealDB.

Resources

recipes://cuisines

List all available recipe collections in the database.

recipes://{cuisine}

Get detailed information about recipes in a specific cuisine collection.

Example: recipes://italian, recipes://pasta

recipes://meal-plans

View all saved meal plans with their details.

recipes://stats

Get comprehensive statistics about the recipe collection.

Prompts

generate_recipe_search_prompt(cuisine_type: str, num_recipes: int = 5)

Generate a comprehensive prompt for recipe search and culinary analysis.

generate_meal_planning_prompt(meal_type: str, people_count: int = 4, dietary_restrictions: str = "none")

Create a detailed meal planning prompt with shopping lists and preparation guides.

generate_cooking_lesson_prompt(skill_level: str, technique_focus: str, cuisine_style: str = "any")

Design structured cooking lessons focused on specific techniques.

generate_ingredient_exploration_prompt(main_ingredient: str, cooking_styles: str = "diverse", num_recipes: int = 6)

Explore recipes and techniques featuring a specific ingredient.

generate_cultural_cuisine_prompt(cuisine_name: str, cultural_context: str = "traditional", num_recipes: int = 5)

Explore the cultural heritage and traditions of specific cuisines.

📁 Data Structure

recipes/
├── <dish_name>/
│   └── recipes_info.json          # Recipe details by dish/cuisine
├── meal_plans/
│   └── <plan_name>.json          # Saved meal plans
├── by_letter/
│   └── letter_<x>_search.json    # Letter-based searches
└── recipe_index.json             # Master recipe index

Recipe Data Format

{
  "recipe_id": {
    "name": "Recipe Name",
    "cuisine": "Italian",
    "category": "Pasta",
    "instructions": "Step by step instructions...",
    "image_url": "https://...",
    "youtube_url": "https://...",
    "source_url": "https://...",
    "ingredients": [
      {
        "ingredient": "Tomatoes",
        "measure": "400g"
      }
    ],
    "tags": ["Vegetarian", "Quick"]
  }
}

🌐 API Integration

This server integrates with TheMealDB free API:

  • Base URL: https://www.themealdb.com/api/json/v1/1
  • Search by name: /search.php?s={dish_name}
  • Search by letter: /search.php?f={letter}
  • Random recipe: /random.php

No API key required for the free tier.

🔧 Development

Code Standards

  • Async/Await: All I/O operations use asyncio and aiofiles
  • HTTP Requests: Use httpx for all web requests
  • Path Handling: Use Pathlib for cross-platform compatibility
  • Error Handling: Comprehensive but not verbose
  • Concurrency: Use asyncio.gather() for parallel operations
  • No Logging: Code should not include logging statements

File Operations

  • All JSON files use UTF-8 encoding with ensure_ascii=False
  • Directory creation uses mode=0o755 for cross-platform compatibility
  • Filename sanitization removes invalid characters for Windows/Mac/Linux compatibility
  • Recipe index automatically rebuilds when stale entries are detected

Deployment

Local Development

  • Uses STDIO transport by default
  • Suitable for MCP client integration

Remote Deployment

  • Set PORT environment variable
  • Server binds to 0.0.0.0 for external access
  • Uses streamable HTTP transport

📊 Performance Features

  • Concurrent Operations: Recipe processing uses asyncio.gather()
  • Caching: Recipe index provides fast lookups
  • Lazy Loading: Resources load data on-demand
  • Cross-platform: Handles Windows, Mac, and Linux file systems

📄 License

This project is part of an Educational MCP server implementation.

🔗 Related Links

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