by mac999 · MCP Server · ★ 27
LLM, RAG and AI agent development tutorial This repository contains Syllabus for LLM(large language model), RAG(retrieval augmented generation), AI Agent and MCP(Model Context Protocol) class focusing on creative AI agent development, modeling, and computing as the viewpoint of usecase. This repository was developed for AI application practitioners and developers. The colab code, source, presentation and reference with AI tools like below can be used for developing LLM, RAG and AI Agent. If you want to know the LLM, RAG and AI Agent with MCP subjects and materials, refer to the below link.
| Stars | 27 |
| Forks | 11 |
| Language | Jupyter Notebook |
| Category | MCP Server |
| License | MIT |
| Quality Score | 70.4275627409199/100 |
| Last Updated | 2026-07-05 |
| Created | 2025-04-18 |
| Platforms | mcp |
| Est. Tokens | ~19k |
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LLM-RAG-Agent-Tutorial is LLM-RAG-Agent-Tutorial for AI application developers and researchers.. It is categorized as a MCP Server with 27 GitHub stars.
LLM-RAG-Agent-Tutorial is primarily written in Jupyter Notebook. It covers topics such as agent, ai, ax.
You can find installation instructions and usage details in the LLM-RAG-Agent-Tutorial GitHub repository at github.com/mac999/LLM-RAG-Agent-Tutorial. The project has 27 stars and 11 forks, indicating an active community.
LLM-RAG-Agent-Tutorial is released under the MIT license, making it free to use and modify according to the license terms.