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Web Browser Mcp Server
What is Web Browser Mcp Server
The web-browser-mcp-server is a Minimum Control Program (MCP) server implementation that enables web browsing capabilities using BeautifulSoup4, allowing AI models to extract and understand web content.
Use cases
Use cases include enabling AI assistants to browse the web for information, extracting specific data from websites, and automating tasks that require web interaction.
How to use
To use the web-browser-mcp-server, install it via Smithery and configure it to interact with your AI models. Utilize the MCP interface to send requests for content extraction from web pages.
Key features
Key features include smart content extraction using CSS selectors, lightning-fast async processing, rich metadata capture, robust error handling, and cross-platform compatibility.
Where to use
The web-browser-mcp-server can be used in various fields such as AI development, web scraping, data extraction, and automated content generation.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Overview
What is Web Browser Mcp Server
The web-browser-mcp-server is a Minimum Control Program (MCP) server implementation that enables web browsing capabilities using BeautifulSoup4, allowing AI models to extract and understand web content.
Use cases
Use cases include enabling AI assistants to browse the web for information, extracting specific data from websites, and automating tasks that require web interaction.
How to use
To use the web-browser-mcp-server, install it via Smithery and configure it to interact with your AI models. Utilize the MCP interface to send requests for content extraction from web pages.
Key features
Key features include smart content extraction using CSS selectors, lightning-fast async processing, rich metadata capture, robust error handling, and cross-platform compatibility.
Where to use
The web-browser-mcp-server can be used in various fields such as AI development, web scraping, data extraction, and automated content generation.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Content
✨ 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 •
📝 Report Bug
✨ 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:
npx -y @smithery/cli install web-browser-mcp-server --client claude
Installing Manually
Install using uv:
uv tool install web-browser-mcp-server
For development:
# 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:
{
"mcpServers": {
"web-browser-mcp-server": {
"command": "uv",
"args": [
"tool",
"run",
"web-browser-mcp-server"
],
"env": {
"REQUEST_TIMEOUT": "30"
}
}
}
}
For Development:
{
"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:
# 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:
python -m pytest
📄 License
Released under the MIT License. See the LICENSE file for details.
Dev Tools Supporting MCP
The following are the main code editors that support the Model Context Protocol. Click the link to visit the official website for more information.










