Amazon Product Intelligence Agent
Scrapes Amazon product details and reviews, manages local product database, and visualizes intelligence data.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Amazon Product Intelligence Agentfetch product details for ASIN B08N5WRWNW"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Amazon Product Intelligence Agent
An autonomous Model Context Protocol (MCP) server that scrapes Amazon product details and reviews, manages local JSON database storage, and visualizes intelligence data using a rich Prefab UI dashboard.
Features
Asynchronous Scraping: Uses
httpxandBeautifulSoup4to concurrently fetch product metadata (price, title, review count, average rating) and top customer reviews from Amazon.Local Persistence: Provides full CRUD operations for managing product intelligence data in a local JSON database.
Rich Dashboard: Generates a beautiful Prefab UI dashboard to visualize the gathered intelligence.
MCP Standard: Fully compatible with any Model Context Protocol client using
fastmcp.
Prerequisites
Python 3.12+ (64-bit recommended)
Node.js (for the MCP Inspector)
Installation
Local Setup
Clone or download the repository.
Open a terminal in the project directory.
Create and activate a virtual environment:
python -m venv venv source venv/Scripts/activate # On Windows Git Bash # OR: .\venv\Scripts\activate # On Windows PowerShellInstall dependencies:
pip install -r requirements.txt
Online Setup (Replit / GitHub Codespaces)
If you cannot install the dependencies locally, you can use a cloud IDE:
Upload the files to Replit or a GitHub Codespace.
Run the installation command in the provided terminal:
pip install -r requirements.txt.
Usage & Testing
The easiest way to test the agent's capabilities is using the official MCP Inspector.
Start the inspector:
npx @modelcontextprotocol/inspector python server.pyOpen the provided localhost URL in your browser.
Navigate to the Tools tab to test the following functions:
fetch_amazon_product: Use an ASIN (likeB08N5WRWNW) to scrape data.manage_product_database: Save the scraped JSON data to your local database.show_product_dashboard: View the generated UI for your saved ASIN.
Ex: https://www.amazon.in/Amazon-Brand-Presto-Oxo-Biodegradable-Garbage/dp/B0821PN8L4/ref=zg_bs_c_kitchen_d_sccl_1/259-9731870-4167526?pd_rd_w=cfXa7&content-id=amzn1.sym.b908f532-cbe7-4274-8b24-b671acc58bd2&pf_rd_p=b908f532-cbe7-4274-8b24-b671acc58bd2&pf_rd_r=F8ZX5X2ZT11NKKGT6PXC&pd_rd_wg=wuSNK&pd_rd_r=b24b1a45-e140-4aad-bc3c-4f47f6ec477e&pd_rd_i=B0821PN8L4&th=1
ASIN is B0821PN8L4
Integrating with an LLM Client
Add the server to your MCP-compatible client (e.g., Claude Desktop) configuration:
{
"mcpServers": {
"amazon-intelligence": {
"command": "python",
"args": ["/absolute/path/to/server.py"]
}
}
}This server cannot be installed
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