# Amazon Product Search MCP Server
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An MCP (Model Context Protocol) server that provides AI-powered Amazon product search and recommendations using FastMCP.
## Features
- 🔍 Smart product search with Amazon API
- 🤖 AI-powered product recommendations using Hugging Face
- 💰 Price range filtering
- 📋 Feature-based matching
- 🎯 Tailored recommendations for Small/Medium Enterprises
## Installation
1. Clone this repository and navigate to the project directory
2. Install dependencies:
```bash
# Using uv (recommended)
uv sync
# Or using pip
pip install -r requirements.txt
```
## Server Setup
### Running the MCP Server
```bash
# Activate your virtual environment
source .venv/bin/activate # On Windows: .venv\Scripts\activate
# Run the server
python main.py
```
The server exposes one main tool:
- `getdata`: Search Amazon products with AI recommendations
## Client Options
We provide multiple client implementations to interact with your MCP server:
### 1. Python Interactive Client (`client.py`)
A full-featured Python client with examples and interactive mode.
```bash
python client.py
```
Features:
- Pre-built examples (laptops, smartphones)
- Interactive search mode
- Real-time communication with MCP server
### 2. Command Line Interface (`cli_client.py`)
Quick command-line searches for automation and scripting.
```bash
# Basic search
python cli_client.py "laptop"
# With features and price range
python cli_client.py "laptop" --features "8GB RAM, SSD storage" --min-price 30000 --max-price 80000
# Smartphone search
python cli_client.py "smartphone" --features "good camera, 5G" --min-price 15000 --max-price 50000
```
Arguments:
- `product`: Product to search for (required)
- `--features`, `-f`: Specific features to look for
- `--min-price`, `-min`: Minimum price in rupees
- `--max-price`, `-max`: Maximum price in rupees
### 3. Web Interface (`web_client.py`)
A beautiful web interface with REST API backend.
```bash
# Install additional dependencies
pip install fastapi uvicorn
# Run the web server
python web_client.py
```
Then open http://localhost:8000 in your browser for a user-friendly interface.
API Endpoints:
- `GET /`: Web interface
- `POST /search`: REST API for product search
- `GET /health`: Health check
### 4. MCP CLI Integration
You can also use the MCP CLI to interact with your server:
```bash
# Install MCP CLI if not already installed
pip install mcp
# Connect to your server
mcp connect stdio -- python main.py
```
## Usage Examples
### Example 1: Laptop Search
```json
{
"product": "laptop",
"specific_features": "8GB RAM, SSD storage, good for programming",
"min_price": 30000,
"max_price": 80000
}
```
### Example 2: Smartphone Search
```json
{
"product": "smartphone",
"specific_features": "good camera, long battery life, 5G support",
"min_price": 15000,
"max_price": 50000
}
```
### Example 3: Budget Headphones
```json
{
"product": "wireless headphones",
"specific_features": "noise cancellation, comfortable",
"min_price": 1000,
"max_price": 5000
}
```
## Configuration
### API Keys Required
Make sure you have:
1. **Hugging Face API Token**: Update `HF_API_TOKEN` in `server/buy.py`
2. **RapidAPI Key**: Update the `x-rapidapi-key` in `server/buy.py`
### Customization
You can customize the AI recommendation prompt in the `decision_agent` function in `server/buy.py`.
## Integration with Claude Desktop
To use this MCP server with Claude Desktop, add this configuration to your `claude_desktop_config.json`:
```json
{
"mcpServers": {
"amazon-search": {
"command": "python",
"args": ["path/to/your/main.py"],
"env": {}
}
}
}
```
## Troubleshooting
### Common Issues
1. **Import errors**: Make sure you're in the correct virtual environment
2. **API failures**: Check your API keys and internet connection
3. **Connection issues**: Ensure the MCP server is running before starting clients
### Error Messages
- "No result": Usually indicates API issues or no products found
- "Connection refused": MCP server is not running
- "Tool not found": Server initialization issue
## Development
### Adding New Features
1. Add new tools in `server/buy.py` using the `@mcp.tool()` decorator
2. Update client code to use new tools
3. Test with the interactive client first
### Testing
```bash
# Test the server directly
python -c "from server.buy import mcp; print('Server loads successfully')"
# Test with the interactive client
python client.py
```
## Architecture
```
┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐
│ MCP Client │◄──►│ MCP Server │◄──►│ External APIs │
│ (Your Choice) │ │ (FastMCP) │ │ (Amazon/HF AI) │
└─────────────────┘ └─────────────────┘ └─────────────────┘
│ │ │
▼ ▼ ▼
┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐
│ • client.py │ │ • Tool: getdata │ │ • Amazon Search │
│ • cli_client │ │ • AI Agent │ │ • HuggingFace │
│ • web_client │ │ • FastMCP │ │ • Recommendations│
│ • Claude │ │ │ │ │
└─────────────────┘ └─────────────────┘ └─────────────────┘
```
## License
This project is open source. Please ensure you comply with the terms of service of the APIs used (Amazon, RapidAPI, Hugging Face).
