fedilahbib/MCP-server-using-FastMCP

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

Installation

1. Create a virtual environment

python3 -m venv venv
source venv/bin/activate

2. Install dependencies

pip install -r requirements.txt

Running the Server

Start the MCP server:

python main.py

The server will start on:

http://localhost:8000

Available 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.py