Q4_learning: This repository is the comprehensive workspace for Quarter 4 academic endeavors, focusing on advanced prompt engineering, specification-driven development, Model Context Protocol, agentic AI, and cloud-native development. It includes assignments, technical documentation, experimental implementations, and applied projects. Primary development languages are Python, TypeScript, and Markdown.; MCP-Chinese-Getting-Started-Guide: This guide provides a rapid introduction to the Model Context Protocol (MCP), an open-source protocol standardizing LLM interactions with external data and tools. It demonstrates building and debugging MCP servers, developing MCP clients for LLMs like DeepSeek, and integrating with Claude Desktop.
Academic assignments and projects in agentic AI
Enhancing LLMs with real-time web search capabilities