MCP Web Analyzer Agent 🌐🤖

An AI-powered web analysis and intelligence platform built on the Model Context Protocol (MCP), Playwright, OpenRouter AI (LLM), Express, and Next.js.

🌟 Highlights & Features

• MCP-Native Architecture: Integrates with the official Model Context Protocol (@modelcontextprotocol/sdk) exposing modular tools for dynamic web scraping, semantic analysis, and structured reporting.

• Deep Web Scraping & Crawling: Uses Playwright and Cheerio for headless browser rendering, single-page application (SPA) support, and multi-page crawl discovery.

• AI-Driven Intelligence: Powered by OpenRouter AI (e.g. GPT-4o-mini) to generate comprehensive SEO audits, readability scores, competitive intelligence, and structural insights.

• Modern Interactive UI: Sleek, high-performance dashboard created with Next.js 14, TypeScript, Lucide icons, and real-time analysis status updates.

• Persistent Storage: Robust PostgreSQL integration with Docker Compose setup for storing crawled pages, analysis history, and metadata.

Related MCP server: SaytLupa

🏗️ Architecture

mcp_webanalyzer/
├── docker-compose.yml       # PostgreSQL database container configuration
├── package.json             # Root workspace script definitions
├── start.bat                # Windows 1-click startup script
├── mcp_backend/             # MCP Server & REST API backend
│   ├── src/
│   │   ├── analyzer.ts      # Web crawler & deep parsing engine
│   │   ├── aiClient.ts      # OpenRouter / LLM analysis integration
│   │   ├── db.ts            # PostgreSQL queries & migrations
│   │   ├── server.ts        # Express server & MCP endpoint handlers
│   │   ├── routes/          # REST endpoints
│   │   └── tools/           # Registered MCP tools
│   ├── .env.example
│   └── package.json
└── frontend/                # Next.js 14 web client
    ├── app/                 # Next.js App Router (pages & layouts)
    ├── components/          # Reusable UI widgets & cards
    ├── .env.example
    └── package.json

🚀 Quick Start

1. Prerequisites

• Node.js 18+ & npm

• Docker & Docker Compose (for PostgreSQL database)

• OpenRouter API Key (or compatible OpenAI-compatible endpoint)

2. Environment Setup

Backend:

Copy the example environment file in mcp_backend:

cd mcp_backend
cp .env.example .env

Open mcp_backend/.env and supply your OPENROUTER_API_KEY and database credentials:

PORT=4000
DATABASE_URL=postgresql://postgres:postgres@localhost:5432/mcp_webanalyzer
OPENROUTER_API_KEY=your_key_here
AI_MODEL=openai/gpt-4o-mini
FRONTEND_URL=http://localhost:3000

Frontend:

Copy the example environment file in frontend:

cd ../frontend
cp .env.example .env.local

3. Database Initialization

Start the PostgreSQL service using Docker:

docker-compose up -d

4. Install Dependencies

Install root, backend, and frontend packages:

# Backend dependencies (and install Playwright browser binaries)
cd mcp_backend
npm install
npx playwright install chromium

# Frontend dependencies
cd ../frontend
npm install

5. Running the Application

Option A: One-Click Launch (Windows)

Double-click start.bat or run:

start.bat

Option B: Manual Startup

From the project root:

# Terminal 1: Start Backend (Port 4000)
npm run dev:backend

# Terminal 2: Start Frontend (Port 3000)
npm run dev:frontend

Open http://localhost:3000 in your browser to start analyzing URLs.

🛠️ MCP Tools Exposed

📄 License

This project is licensed under the MIT License.