| File Name: | Agentic AI Engineering with MERN: RAG, MCP & AI Agents |
| Content Source: | https://www.udemy.com/course/agentic-ai-engineering-with-mern-rag-mcp-ai-agents/ |
| Genre / Category: | Ai Courses |
| File Size : | 21.8 GB |
| Publisher: | Nikhil Agarwal |
| Updated and Published: | January 15, 2026 |
Stop building basic chatbots. It is time to build intelligent AI Agents that can actually do things. Welcome to the Agentic AI Engineering program, the only course you need to bridge the gap between simple LLM wrappers and complex, production-ready Agentic Systems. Most developers are stuck building “chat with PDF” apps. In this course, we go levels deeper. You will architect a Full-Stack Agentic Application from scratch using React and Node.js, integrating cutting-edge protocols like MCP (Model Context Protocol) and advanced RAG pipelines.
Why this course? The industry is shifting from “Generative AI” to “Agentic AI.” Companies don’t just want text; they want Agents that can query databases, execute tools, and perform actions. This course puts you ahead of that curve.
What you will build: We will engineer a professional-grade AI platform with a modern React UI and a robust Node.js/Express backend. You won’t just learn syntax; you will learn the architecture behind autonomous systems.
Key Technical Deep Dives:
- The Model Context Protocol (MCP): Be one of the first to master this standard. You will build Custom MCP Servers in Node.js to connect your AI to real-world data (like Weather APIs) and expose them as tools to Claude, Gemini, or OpenAI.
- Advanced RAG Pipelines: Move beyond basics. We implement Vector Search using ChromaDB and pgVector, handling embeddings, chunking, and ingestion manually to give you total control.
- Native Tool Calling: Learn how to make LLMs (Gemini & OpenAI) strictly structured JSON to trigger functions in your code—the backbone of Agentic AI.
- Math & Theory: We don’t just import libraries. We cover the logic behind Cosine Similarity, Vector spaces, and Retrieval scoring so you understand why your retrieval works.
The Tech Stack:
- Frontend: React (Latest), TailwindCSS, Vite
- Backend: Node.js, Express, TypeScript
- AI Models: Google Gemini, OpenAI GPT Models
- Vector Databases: ChromaDB, pgVector (PostgreSQL)
- Protocols: MCP (Model Context Protocol)
If you are ready to stop playing with toys and start building intelligent, agentic systems, enroll now. Let’s write some code.
DOWNLOAD LINK: Agentic AI Engineering with MERN: RAG, MCP & AI Agents
Agentic_AI_Engineering_with_MERN_RAG_MCP_AI_Agents.part01.rar – 1000.0 MB
Agentic_AI_Engineering_with_MERN_RAG_MCP_AI_Agents.part02.rar – 1000.0 MB
Agentic_AI_Engineering_with_MERN_RAG_MCP_AI_Agents.part03.rar – 1000.0 MB
Agentic_AI_Engineering_with_MERN_RAG_MCP_AI_Agents.part04.rar – 1000.0 MB
Agentic_AI_Engineering_with_MERN_RAG_MCP_AI_Agents.part05.rar – 1000.0 MB
Agentic_AI_Engineering_with_MERN_RAG_MCP_AI_Agents.part06.rar – 1000.0 MB
Agentic_AI_Engineering_with_MERN_RAG_MCP_AI_Agents.part07.rar – 1000.0 MB
Agentic_AI_Engineering_with_MERN_RAG_MCP_AI_Agents.part08.rar – 1000.0 MB
Agentic_AI_Engineering_with_MERN_RAG_MCP_AI_Agents.part09.rar – 1000.0 MB
Agentic_AI_Engineering_with_MERN_RAG_MCP_AI_Agents.part10.rar – 1000.0 MB
Agentic_AI_Engineering_with_MERN_RAG_MCP_AI_Agents.part11.rar – 1000.0 MB
Agentic_AI_Engineering_with_MERN_RAG_MCP_AI_Agents.part12.rar – 1000.0 MB
Agentic_AI_Engineering_with_MERN_RAG_MCP_AI_Agents.part13.rar – 1000.0 MB
Agentic_AI_Engineering_with_MERN_RAG_MCP_AI_Agents.part14.rar – 1000.0 MB
Agentic_AI_Engineering_with_MERN_RAG_MCP_AI_Agents.part15.rar – 1000.0 MB
Agentic_AI_Engineering_with_MERN_RAG_MCP_AI_Agents.part16.rar – 1000.0 MB
Agentic_AI_Engineering_with_MERN_RAG_MCP_AI_Agents.part17.rar – 1000.0 MB
Agentic_AI_Engineering_with_MERN_RAG_MCP_AI_Agents.part18.rar – 1000.0 MB
Agentic_AI_Engineering_with_MERN_RAG_MCP_AI_Agents.part19.rar – 1000.0 MB
Agentic_AI_Engineering_with_MERN_RAG_MCP_AI_Agents.part20.rar – 1000.0 MB
Agentic_AI_Engineering_with_MERN_RAG_MCP_AI_Agents.part21.rar – 1000.0 MB
Agentic_AI_Engineering_with_MERN_RAG_MCP_AI_Agents.part22.rar – 819.8 MB
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