ai-webscraper-agent

🕸️ AI Webscraper Agent

An AI-powered webscraping agent that uses the Brightdata MCP server to extract and summarize content from the web. Built with a modular architecture combining LLM reasoning, robust scraping, and a simple web interface.

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🔧 Tech Stack

• Frontend: Streamlit
• Backend: FastAPI
• Language: Python
• Scraping: Brightdata MCP Server
• AI Model: Anthropic LLM (Claude)

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🚀 Features

• Natural language interface to extract data from websites
• Uses Brightdata MCP for reliable web scraping
• LLM-powered summarization and reasoning
• Streamlit-based interactive frontend
• Async FastAPI backend integration

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Environment Variables

Create a .env file and configure the following:

# .env
# Environment Variables for AI Webscraper Agent
# Replace 'your_key_here' with your actual API keys

# Bright Data
API_TOKEN=your_key_here
WEB_UNLOCKER_ZONE=your_key_here
BROWSER_AUTH="your_browser_auth_token"

#Anthropic AI API KEY
ANTHROPIC_API_KEY=your_key_here

📦 Installation

git clone https://github.com/yourusername/ai-webscraper-agent.git
cd ai-webscraper-agent

uv pip install -r requirements.txt

RUN App

Start the FastAPI backend server and Streamlit app'

Start the backend FastAPI server

uv run backend.py

Start frontend Streamlit app

streamlit run frontend.py

Example Usage

Ask:

Scrape the top 5 news headlines from https://bbc.com and summarize them.

Get Response:

1. Headline A - Summary
2. Headline B - Summary
3. Headline C - Summary
4. Headline C - Summary
...

Agent Flow

[User Prompt] ➡ [Streamlit UI] ➡ [FastAPI Router] ➡ [LLM Agent]
➡ [Brightdata Tool via MCP] ➡ [LLM Summarization] ➡ [UI Response]