Prepare the server locally
Run this once before adding it to Claude Code.
git clone https://github.com/FassihShah/PriceHunt-MCP.git
cd PriceHunt-MCP
uv installRegister it in Claude Code
claude mcp add -e "GOOGLE_API_KEY=${GOOGLE_API_KEY}" ecommerce-product-hunt -- python /path/to/your/project/mcp_server.pyReplace any placeholder paths in the command with the real path on your machine.
GOOGLE_API_KEYMake your agent remember this setup
ecommerce-product-hunt's config, env vars, and the gotchas you hit — recalled in every future Claude Code, Cursor, and Codex session.
npx conare@latestFree · one command · indexes the sessions already on disk. Set up in the browser instead →
What it does
- Multi-platform search across Daraz, Telemart, and iShopping
- Quality filtering for products with 4+ star ratings
- Price-focused search to find the lowest-priced genuine products
- AI-powered intelligent product matching
Tools 3
get_daraz_productsScrapes Daraz with 4+ rating filterget_telemart_productsScrapes Telemart search resultsget_ishopping_productsScrapes iShopping catalogEnvironment Variables
GOOGLE_API_KEYrequiredAPI key for Google Gemini integrationTry it
Original README from SyedHussainAhmad/e-Commerce-Product-Hunt
🛍️ E-Commerce Product Hunt
A Model Context Protocol (MCP) implementation that finds the lowest-priced products with good ratings (4+ stars) across major Pakistani e-commerce platforms including Daraz, Telemart, and iShopping.
MCP
Model Context Protocol (MCP) is a standardized protocol that enables AI applications to securely connect to external data sources and tools. It acts as a bridge between AI models (like Gemini) and various services, databases, APIs, and applications.
MCP Architecture Components:
- MCP Servers - Provide specific tools, resources, or data to clients
- MCP Clients - AI applications that want to access external resources
- Transport Layer - Communication mechanism between clients and servers
🎯 Project Overview
This project demonstrates MCP implementation by creating:
- MCP Server: Provides three tools for scraping Pakistani e-commerce sites
- MCP Client: Uses LangChain + Google Gemini to orchestrate tool calls
- Streamlit Frontend: User-friendly web interface for product searches
Note: In this project both server and client run on the same host for learning purposes.
✨ Features
- 🔍 Multi-Platform Search: Scrapes Daraz, Telemart, and iShopping simultaneously
- ⭐ Quality Filtering: Prioritizes products with 4+ star ratings
- 💰 Price Search: Finds the lowest-priced genuine products
- 🤖 AI-Powered: Uses Google Gemini for intelligent product matching
- 💬 Chat Interface: Conversational UI with memory
- 🚀 Async Processing: Non-blocking operations for better performance
🏛️ MCP Architecture
This Project's MCP Implementation:
┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐
│ Streamlit │ │ MCP Client │ │ MCP Server │
│ Frontend │◄──►│ (LangChain + │◄──►│ (FastMCP) │
│ (app.py) │ │ Gemini) │ │ │
└─────────────────┘ └─────────────────┘ └─────────────────┘
│
▼
┌─────────────────┐
│ E-commerce │
│ Websites │
│ • Daraz.pk │
│ • Telemart.pk │
│ • iShopping.pk │
└─────────────────┘
MCP Tools Defined:
get_daraz_products(query)- Scrapes Daraz with 4+ rating filterget_telemart_products(query)- Scrapes Telemart search resultsget_ishopping_products(query)- Scrapes iShopping catalog
📁 Project Structure
PriceHunt-MCP/
├── project/ # Client-side code
│ └── app.py # Streamlit web interface
| └── mcp_client.py # MCP Client with LangChain integration
| └── mcp_server.py # MCP Server with 3 e-commerce tools
├── python-version # Python version specification
├── pyproject.toml # Python project configuration
├── README.md # This file
└── uv.lock # UV dependency lock file
🚀 Installation & Setup
1. Clone the Repository
git clone https://github.com/FassihShah/PriceHunt-MCP.git
cd PriceHunt-MCP
2. Create Virtual Environment
# Create virtual environment
python -m venv venv
# Activate virtual environment
venv\Scripts\activate
3. Install Dependencies
Since we're using uv, install dependencies with:
# If using uv (recommended)
uv install
# Or using pip with requirements.txt
pip install -r requirements.txt
If you don't have uv installed:
# Install uv first
pip install uv
# Then install dependencies
uv install
4. Set Up Environment Variables
Create a .env file in the project root:
GOOGLE_API_KEY=your_google_gemini_api_key_here
🖥️ Using with Claude Desktop
This MCP server can also be integrated directly with Claude Desktop application, allowing to use the e-commerce tools directly in your conversations with Claude!
Setup for Claude Desktop:
1. Install Claude Desktop:
- Download from Claude Desktop
- Make sure you have the latest version
2. Configure Claude Desktop: Open the Claude Desktop configuration file:
Windows:
code %APPDATA%\Claude\claude_desktop_config.json
3. Add Your MCP Server:
Create or update the claude_desktop_config.json file:
{
"mcpServers": {
"ecommerce-scraper": {
"command": "python",
"args": ["/path/to/your/project/mcp_server.py"],
"env": {
"PYTHONPA