MCP Food Search

🚀 Grocery Search MCP Server

An MCP (Model Context Protocol) server that enables searching for grocery prices and nutritional information. It empowers AI agents to search for food products, compare prices, and analyze nutritional content across various grocery stores.

🚀 Quick Start

This Grocery Search MCP Server offers a way to search grocery price and nutritional information. You can start using it by following the installation and usage steps below.

✨ Features

• Product Search: Search for grocery items by name across supported stores.
• Price Comparison: Obtain current pricing information for food products.
• Nutritional Analysis: Retrieve protein, calorie, and other macro information.
• Protein-per-Dollar Ranking: Automatically rank products by protein content per dollar spent.
• Store Support: Currently supports Trader Joe's (more stores coming soon).

📦 Installation

Clone the Repository

git clone <repository-url>
cd MCP_Food_Search

Install Dependencies

pip install -r requirements.txt

Install in Development Mode

pip install -e .

💻 Usage Examples

Running the MCP Server

python -m grocery_search_mcp.server

Or using the script entry point:

grocery-search-mcp

Testing the Implementation

python test_server.py

MCP Tool Usage

The server provides one main tool:

GroceryPrices.search

Search for grocery items with price and nutritional information.

Parameters:

• query (required): Food or product name to search for.
• store (optional): Store to search, defaults to "trader_joes".

Example:

{
  "query": "protein bar",
  "store": "trader_joes"
}

Response: Returns a formatted list of products with:

• Product name and brand.
• Price and package size.
• Protein content and calories.
• Protein-per-dollar ratio.
• Nutritional information status.

🔧 Technical Details

Architecture

The server consists of several key components:

• MCP Server (server.py): Main MCP protocol implementation.
• Data Models (models.py): Pydantic models for requests/responses.
• Scrapers (scraper.py): Web scraping logic for different stores.
• Nutrition Estimation: Basic nutritional information estimation.

Current Implementation

This initial version includes:

• ✅ Basic MCP server setup.
• ✅ Trader Joe's product search (mock data for now).
• ✅ Nutritional estimation based on product names.
• ✅ Protein-per-dollar calculation.
• ✅ Error handling and logging.

Future Enhancements

• Real web scraping implementation.
• Integration with USDA FoodData Central API.
• Redis caching for price data.
• Additional store support (Safeway, Kroger, etc.).
• Real-time inventory checking.
• Advanced nutritional analysis.

🤝 Contributing

This is a learning project. Feel free to submit issues and enhancement requests.

📄 License

MIT License