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Grocery Search
- python
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python
Language
7 months ago
First Indexed
3 months ago
Catalog Refreshed
Documentation & install
Readme and setup notes from the catalogue, plus a client-ready config you can copy for your MCP host.
Installation
Add the following to your MCP client configuration file.
Configuration
View docs{
"mcpServers": {
"ajaykallepalli-mcp_food_search": {
"command": "python",
"args": [
"-m",
"grocery_search_mcp.server"
]
}
}
}You can run and query the Grocery Search MCP Server to find grocery items, compare prices, and see nutritional information across supported stores. This server exposes a single, focused tool that powers AI agents to search for products, analyze nutrition, and rank protein value per dollar, all through the MCP interface.
How to use
To use the Grocery Prices search tool, connect your MCP client to the server and call the GroceryPrices.search endpoint. You can provide a product name to search for and optionally specify a store to narrow results. The tool will return a list of matching products with their price, package size, protein content, calories, and a protein-per-dollar ranking. Use cases include finding high-protein items for a specific budget, comparing prices across stores, and assessing overall nutritional value.
How to install
Prerequisites: ensure you have Python installed on your system.
Step 1: Clone the repository locally.
git clone <repository-url>
cd MCP_Food_Search
Step 2: Install dependencies.
pip install -r requirements.txt
Step 3: Install in development mode (optional but common during active development).
pip install -e .
Step 4: Start the MCP server using the standard Python invocation or the script entry point.
python -m grocery_search_mcp.server
grocery-search-mcp
Testing the implementation
Validate the server by running the provided test script to verify functionality.
python test_server.py
Available tools
GroceryPrices.search
Search for grocery items and obtain price, nutrition data, and protein-per-dollar calculations. Returns item details including name, brand, price, package size, protein, calories, and nutritional status.