Product MCP Server
This server does not currently have a deployable release on Glama. Follow the repository's setup instructions to install and configure it for your MCP client, including any required credentials and local dependencies.
Product MCP Server
This project implements a simple Model Context Protocol (MCP) server using FastMCP, Pydantic, and Uvicorn.
It exposes three tools:
Add Product
Search Product
Get Product by ID
Products are stored in an in-memory database, making this ideal for demos, prototyping, or integrating with an MCP-compatible AI agent.
Features
FastMCP-based MCP server
Tool functions to:
Add a new product
Search products by name or category
Retrieve product details by ID
Simple in-memory storage
Runs over HTTP using Uvicorn
Related MCP server: MCP Inventario
Installation
1. Create a virtual environment
python3 -m venv venv
source venv/bin/activate2. Install dependencies
pip install -r requirements.txtRunning the Server
Start the MCP server:
python main.pyThe server will start on:
http://localhost:8000Available Tools
1. add_product
Adds a new product to the in-memory catalog.
Input Model (AddProductInput)
{
"name": "Laptop",
"category": "Electronics",
"price": 1299.99,
"stock": 5,
"description": "Powerful gaming laptop"
}2. search_product
Searches for products by name or category.
Input Model (SearchInput)
{
"query": "laptop"
}3. get_product
Gets a product by its unique ID.
Input Model (GetProductInput)
{
"product_id": "uuid-here"
}MCP Client Example
Run the client
python client.pyThis server cannot be deployed
Maintenance
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