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## ✨ Features > 🌐 Enable AI assistants to browse and extract content from the web through a simple MCP interface. The Web Browser MCP Server provides AI models with the ability to browse websites, extract content, and understand web pages through the Message Control Protocol (MCP). It enables smart content extraction with CSS selectors and robust error handling.

🤝 **[Contribute](https://github.com/blazickjp/web-browser-mcp-server/blob/main/CONTRIBUTING.md)** • 📝 **[Report Bug](https://github.com/blazickjp/web-browser-mcp-server/issues)**

## ✨ Core Features - 🎯 **Smart Content Extraction**: Target exactly what you need with CSS selectors - ⚡ **Lightning Fast**: Built with async processing for optimal performance - 📊 **Rich Metadata**: Capture titles, links, and structured content - 🛡️ **Robust & Reliable**: Built-in error handling and timeout management - 🌍 **Cross-Platform**: Works everywhere Python runs ## 🚀 Quick Start ### Installing via Smithery To install Web Browser Server for Claude Desktop automatically via [Smithery](https://smithery.ai/server/web-browser-mcp-server): ```bash npx -y @smithery/cli install web-browser-mcp-server --client claude ``` ### Installing Manually Install using uv: ```bash uv tool install web-browser-mcp-server ``` For development: ```bash # Clone and set up development environment git clone https://github.com/blazickjp/web-browser-mcp-server.git cd web-browser-mcp-server # Create and activate virtual environment uv venv source .venv/bin/activate # Install with test dependencies uv pip install -e ".[test]" ``` ### 🔌 MCP Integration Add this configuration to your MCP client config file: ```json { "mcpServers": { "web-browser-mcp-server": { "command": "uv", "args": [ "tool", "run", "web-browser-mcp-server" ], "env": { "REQUEST_TIMEOUT": "30" } } } } ``` For Development: ```json { "mcpServers": { "web-browser-mcp-server": { "command": "uv", "args": [ "--directory", "path/to/cloned/web-browser-mcp-server", "run", "web-browser-mcp-server" ], "env": { "REQUEST_TIMEOUT": "30" } } } } ``` ## 💡 Available Tools The server provides a powerful web browsing tool: ### browse_webpage Browse and extract content from web pages with optional CSS selectors: ```python # Basic webpage fetch result = await call_tool("browse_webpage", { "url": "https://example.com" }) # Target specific content with CSS selectors result = await call_tool("browse_webpage", { "url": "https://example.com", "selectors": { "headlines": "h1, h2", "main_content": "article.content", "navigation": "nav a" } }) ``` ## ⚙️ Configuration Configure through environment variables: | Variable | Purpose | Default | |----------|---------|---------| | `REQUEST_TIMEOUT` | Webpage request timeout in seconds | 30 | ## 🧪 Testing Run the test suite: ```bash python -m pytest ``` ## 📄 License Released under the MIT License. See the LICENSE file for details. ---

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