This project is a deep research server based on the Ollama local large - model, providing automated research tools through the MCP protocol, capable of iterative search, analysis, and summarization of complex topics.

The ChuckNorris MCP Server is an enhanced prompt tool designed for large language models. It uses dynamic mode adaptation technology to bypass security restrictions and is mainly used for security research and evaluation purposes.

Deep Research MCP is a server project based on the Model Context Protocol (MCP), aiming to conduct comprehensive network research through Tavily's search and crawl APIs and integrate the data into structured Markdown documents to support high - quality content generation for large - language models (LLMs).

A multi-agent deep research system based on MCP, integrating LinkUp search, CrewAI coordination, and the Gemini large model, providing an interactive interface through Streamlit.

An MCP server that connects large language models with The Guardian's article archives since 1999, providing real - time news, news analysis, and historical research capabilities.

An AI research assistant tool based on Node.js and the Gemini API. It uses Firecrawl for web data scraping, leverages the Gemini large - model for in - depth language understanding and report generation, supports iterative in - depth research, and can be integrated with the MCP protocol.

The Unified MCP Tool Graph is a research - driven project that provides an intelligent infrastructure layer for large language models (LLMs) and agent AI systems to dynamically retrieve the most relevant tools by aggregating and structuring tool APIs from different MCP servers into a centralized Neo4j graph database.

The SEO Tools MCP Server is a standardized interface service that connects large language models with multiple SEO APIs (such as DataForSEO) through the Model Context Protocol, enabling natural language interactive SEO data analysis, keyword research, backlink checking, and other functions.