Free Download Agentic AI Engineering with MERN RAG, MCP & AI AgentsPublished 1/2026
Created by Nikhil Agarwal
MP4 |
Video: h264, 1920x1080 |
Audio: AAC, 44.1 KHz, 2 Ch
Level: All |
Genre: eLearning |
Language: English |
Duration: 88 Lectures ( 15h 4m ) |
Size: 21.3 GB
Architect and build a complete Full-Stack (MERN) Agentic AI application using React, Node.js, and Express.
Implement advanced Retrieval Augmented Generation (RAG) pipelines with embeddings, vector search, and context augmentation.
Master the Model Context Protocol (MCP) by building custom MCP Servers in Node.js to expose real-world tools to LLMs.
Build a production-ready Chat Interface in React that handles streaming responses, Markdown rendering, and tool outputs.
Set up and manage Vector Databases (ChromaDB and pgVector) to store high-dimensional embeddings for semantic search.
Create Deterministic RAG Systems using JSON and math-based Cosine Similarity to understand the core algorithms of retrieval.
Implement Native Tool Calling with Gemini and OpenAI to turn natural language into executable code functions.
Connect your RAG Engine as an MCP Tool, creating a modular system where Agents can "choose" to search your database.
RequirementsSolid understanding of JavaScript & TypeScript: You must be comfortable with Async/Await, Promises, and ES6+ syntax.
Basic Node.js & Express: We build a backend API, so you should know how to set up a server and routes.
Frontend Fundamentals: Experience with React is required. We move fast on the UI (using AI-assisted scaffolding)
No AI Experience Needed: I will teach you RAG, Vector DBs, and MCP from the ground up.
DescriptionStop 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, ViteBackend: Node.js, Express, TypeScriptAI Models: Google Gemini, OpenAI GPT ModelsVector 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.
Who this course is forFull-Stack (MERN) Developers who want to transition from traditional web apps to building AI-powered Agentic systems.
Solutions Architects & Tech Leads who need to implement the new Model Context Protocol (MCP) standard in enterprise.
AI Enthusiasts looking to master the Model Context Protocol (MCP) and modern Tool Calling standards.
Software Engineers who need to implement RAG and Vector Search without relying on "black box" frameworks like LangChain.
Freelancers & Consultants who want to offer high-value "Custom AI Agent" services to clients.
Homepagehttps://www.udemy.com/course/agentic-ai-engineering-with-mern-rag-mcp-ai-agents/Recommend Download Link Hight Speed | Please Say Thanks Keep Topic Live
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