| Name | web-browser-mcp JSON |
| Version |
0.1.1
JSON |
| download |
| home_page | None |
| Summary | Transform your AI applications with advanced web browsing capabilities through this Model Context Protocol (MCP) server |
| upload_time | 2024-11-30 18:39:02 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.11 |
| license | MIT |
| keywords |
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# Web Intelligence MCP Server
Transform your AI applications with advanced web browsing capabilities. This Model Context Protocol (MCP) server empowers AI systems to intelligently navigate, extract, and analyze web content with precision and reliability.
## Overview
The Web Intelligence MCP server bridges the gap between AI systems and web content, enabling sophisticated web browsing capabilities through a robust, production-ready API. By leveraging the power of BeautifulSoup4 and modern async processing, it provides AI applications with the ability to understand and extract structured information from any webpage.
## Key Features
The server provides enterprise-grade capabilities for web content processing:
- Intelligent content extraction with customizable CSS selectors
- High-performance asynchronous processing
- Comprehensive metadata capture including titles, links, and structured content
- Robust error handling and timeout management
- Production-ready security features
- Cross-platform compatibility
## Integration with Claude and AI Applications
Seamlessly integrate web browsing capabilities into your AI workflows by adding this configuration to your `claude_desktop_config.json`:
```json
{
"mcpServers": {
"web-intelligence": {
"module": "web-browser-mcp",
"env": {
"REQUEST_TIMEOUT": "30"
}
}
}
}
```
## Enterprise-Ready Features
Our implementation focuses on reliability and security:
- Configurable timeout and retry mechanisms
- Comprehensive error handling
- Rate limiting and resource protection
- Detailed logging and monitoring capabilities
- Production-grade async processing
- Cross-origin request security
## API Example
Extract structured content from web pages with precision:
```python
response = requests.post(
"http://localhost:8000/parse",
json={
"url": "https://example.com",
"selectors": {
"article_content": "article.main-content",
"headlines": "h1.headline",
"metadata": ".meta-tags"
}
}
)
structured_content = response.json()
```
## Development and Testing
We maintain high standards for code quality and testing:
```bash
# Set up development environment
uv venv
source .venv/bin/activate
uv pip install -e ".[test]"
# Run comprehensive test suite
python -m pytest
```
## Security Considerations
The server implements industry-standard security practices:
- Input validation and sanitization
- Secure request handling
- Timeout controls
- Rate limiting
- Error handling without information exposure
## Production Deployment
Deploy with confidence using our production-ready configuration:
```bash
python -m mcp_web_browser.cli --workers 4 --log-level warning
```
## Contributing
We welcome contributions that enhance the server's capabilities. Please review our contributing guidelines and code of conduct.
## License
This project is licensed under the MIT License, providing flexibility for both personal and commercial use.
---
*Empower your AI applications with intelligent web browsing capabilities. Start integrating today.*
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"description": "# Web Intelligence MCP Server\n\nTransform your AI applications with advanced web browsing capabilities. This Model Context Protocol (MCP) server empowers AI systems to intelligently navigate, extract, and analyze web content with precision and reliability.\n\n## Overview\n\nThe Web Intelligence MCP server bridges the gap between AI systems and web content, enabling sophisticated web browsing capabilities through a robust, production-ready API. By leveraging the power of BeautifulSoup4 and modern async processing, it provides AI applications with the ability to understand and extract structured information from any webpage.\n\n## Key Features\n\nThe server provides enterprise-grade capabilities for web content processing:\n\n- Intelligent content extraction with customizable CSS selectors\n- High-performance asynchronous processing\n- Comprehensive metadata capture including titles, links, and structured content\n- Robust error handling and timeout management\n- Production-ready security features\n- Cross-platform compatibility\n\n## Integration with Claude and AI Applications\n\nSeamlessly integrate web browsing capabilities into your AI workflows by adding this configuration to your `claude_desktop_config.json`:\n\n```json\n{\n \"mcpServers\": {\n \"web-intelligence\": {\n \"module\": \"web-browser-mcp\",\n \"env\": {\n \"REQUEST_TIMEOUT\": \"30\"\n }\n }\n }\n}\n```\n\n## Enterprise-Ready Features\n\nOur implementation focuses on reliability and security:\n\n- Configurable timeout and retry mechanisms\n- Comprehensive error handling\n- Rate limiting and resource protection\n- Detailed logging and monitoring capabilities\n- Production-grade async processing\n- Cross-origin request security\n\n## API Example\n\nExtract structured content from web pages with precision:\n\n```python\nresponse = requests.post(\n \"http://localhost:8000/parse\",\n json={\n \"url\": \"https://example.com\",\n \"selectors\": {\n \"article_content\": \"article.main-content\",\n \"headlines\": \"h1.headline\",\n \"metadata\": \".meta-tags\"\n }\n }\n)\n\nstructured_content = response.json()\n```\n\n## Development and Testing\n\nWe maintain high standards for code quality and testing:\n\n```bash\n# Set up development environment\nuv venv\nsource .venv/bin/activate\nuv pip install -e \".[test]\"\n\n# Run comprehensive test suite\npython -m pytest\n```\n\n## Security Considerations\n\nThe server implements industry-standard security practices:\n\n- Input validation and sanitization\n- Secure request handling\n- Timeout controls\n- Rate limiting\n- Error handling without information exposure\n\n## Production Deployment\n\nDeploy with confidence using our production-ready configuration:\n\n```bash\npython -m mcp_web_browser.cli --workers 4 --log-level warning\n```\n\n## Contributing\n\nWe welcome contributions that enhance the server's capabilities. Please review our contributing guidelines and code of conduct.\n\n## License\n\nThis project is licensed under the MIT License, providing flexibility for both personal and commercial use.\n\n---\n\n*Empower your AI applications with intelligent web browsing capabilities. Start integrating today.*",
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