Build AI Agents with CrewAI, MCP and Gemini (Step-by-Step Tutorial + Live Demo)

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👉 Agentic AI Free Webinar Link - https://interviewkickstart.com/agentic-ai-career-boost?utm_source=google&utm_medium=youtube_video&utm_campaign=L10X_social_media_youtube_video_YTV051125&utm_content=youtube_video FREE AI playbook 👉 https://interviewkickstart.com/guide/ai-interview-success-playbook?utm_source=google&utm_medium=youtube_video&utm_campaign=L10X_social_media_youtube_video_YTV051125-2&utm_content=youtube_video In this video, you’ll learn how to build AI Agents using CrewAI, MCP, and Gemini — step by step! 🚀 This tutorial covers everything from setup to a live demo so you can create your own intelligent AI agents that automate real-world tasks. We’ll explore: What is CrewAI and how it works Setting up MCP (Model Context Protocol) for agent coordination Integrating Gemini for enhanced reasoning and task execution Building a full AI workflow combining all three Live demo of a working AI agent project ⏱️ Chapters / Timestamps 00:00 – Intro: Welcome to the Session 00:52 – Agenda: What You’ll Learn Today 02:00 – What Is Agentic AI? (Basics Explained) 04:41 – Evolution of LLMs → Agentic AI (2022–2025) 09:18 – Types of AI Agents (Reactive, Cognitive, Specialized) 14:23 – Building Robust Agentic Systems (Safety, Scaling & Integration) 17:43 – 7 Core Components of Agentic AI Systems 20:35 – Perception, Planning & Memory (with RAG Concepts) 25:29 – Reasoning & Decision-Making (ReAct, ReWOO, Heuristics) 31:06 – Tool Calling, Action & Real-World Execution 33:33 – Communication & Learning in AI Agents 33:33 – Six Design Patterns for Agentic AI (Prompt Chaining, Routing, Reflection & More) 47:01 – Multi-Agent Collaboration Models (Manager, Hierarchy, Network) 53:03 – What is MCP? (Model Context Protocol Explained) 59:00 – 🧠 Live Demo: Build an AI Job Finder Agent (CrewAI + Gemini + MCP) 01:00:35 – Demo Features & Agent Roles 01:03:00 – Python Config Setup (Job Title, Skills, Salary, Location) 01:04:00 – Running the CrewAI Orchestration 01:05:00 – Real-Time Agent Execution (Serper API + Gemini) 01:07:00 – Demo Output Review & Results 01:09:55 – Key Takeaways: Components + Patterns Recap 01:11:34 – Closing Thoughts & Agentic AI Program at Interview Kickstart 🔧 Tools & Frameworks Used CrewAI → Multi-agent orchestration MCP → Model Context Protocol for tool integration Google Gemini → LLM for reasoning and generation Serper API → Web data retrieval Python → Runtime for agent logic Whether you’re a developer, AI enthusiast, or tech creator, this tutorial will help you understand how to connect multiple AI systems into one powerful agent architecture. By the end, you’ll be able to build your own AI automation system using CrewAI, MCP, and Gemini. 💡 Topics Covered: CrewAI installation and configuration Setting up MCP environment Integrating Gemini with MCP Creating autonomous workflows Real-time agent demo Best practices for scalability and performance 📘 What You’ll Learn: Build an AI agent step-by-step How CrewAI manages multiple sub-agents How MCP standardizes communication between models How Gemini enhances decision-making in AI workflows How to deploy and test your AI agent in real time If you want to stay ahead in the AI revolution, make sure to watch till the end, like, subscribe, and turn on notifications 🔔 for more tutorials on AI tools, agents, and automation. #AI #CrewAI #Gemini #MCP #ArtificialIntelligence #Automation #AITutorial #AIAgents #GoogleGemini #CrewAIProjects #BuildAIAgents #OpenSourceAI #AgentFramework #MachineLearning #AITools #TechTutorial #AIDemo #StepByStepTutorial