Deep Web Research
CreatedPedroDnT
Enhances web research capabilities for large language models through intelligent search queuing and content extraction.
About
Deep Web Research is a Model Context Protocol (MCP) server designed to enhance the web research capabilities of large language models like Claude. By providing intelligent search queuing, enhanced content extraction, and deep research capabilities, it allows for real-time information integration into conversational AI workflows. Features include advanced search result processing with TF-IDF relevance scoring, keyword proximity analysis, and improved HTML parsing, optimized for overcoming the limitations of standard search and information retrieval in a conversational context.
Key Features
- Google search integration and webpage content extraction
- 0 GitHub stars
- Enhanced content extraction with TF-IDF relevance scoring and keyword proximity analysis
- Support for parallel searches with intelligent queuing
- Intelligent search queue system with batch operations and rate limiting
- Structured data extraction and content cleaning
Use Cases
- Automated knowledge gathering for AI agents
- Real-time information integration into Claude
- Comprehensive web research for LLMs