Explore a 20-minute presentation from Discover AI about ALITA, an unscripted agent evolution system utilizing the MCP toolbox. Learn about this generalist agent designed for scalable agentic reasoning with minimal predefinition and maximal self-evolution. The talk covers the RAG-MCP paper, which addresses prompt bloat in LLM tool selection through Retrieval-Augmented Generation. Developed by researchers from Princeton University, Tsinghua University, Shanghai Jiao Tong University, University of Michigan, Tianqiao and Chrissy Chen Institute, The Chinese University of Hong Kong, Beijing University of Post and Communications, and Queen Mary University of London, this presentation provides valuable insights into cutting-edge AI agent technology, research developments, and coding applications.