CrewAI Tools, MCP, and Agentic RAG

This program introduces you to CrewAI Tools, MCP, and Agentic RAG, designed for developers and AI practitioners looking to build intelligent, production-ready multi-agent systems. You’ll begin by exploring how agents use tools to interact with external systems, including CrewAI’s built-in tools and custom tool development for real-world workflows. Next, you’ll dive into memory and knowledge systems, learning how agents store, retrieve, and prioritize information across interactions. You’ll explore Agentic RAG to build knowledge-driven agents that retrieve relevant data and generate accurate, context-aware responses. Through hands-on demonstrations, you will design systems that combine memory and retrieval to improve reliability and reduce hallucinations. As you progress, you’ll focus on extending agents using the Model Context Protocol (MCP). You’ll learn how agents discover and interact with tools dynamically through MCP servers, enabling structured communication and scalable system design. You’ll also implement role-based access control, authentication, and secure workflows to ensure safe and controlled agent behavior in real-world environments. By the end of the program, you will be able to: - Identify how tools extend agent capabilities and enable structured workflows in CrewAI. - Apply memory systems and Agentic RAG to build context-aware and knowledge-driven agents. - Analyze how agents retrieve and use knowledge to improve accuracy and reduce hallucinations. - Integrate MCP to enable dynamic tool discovery and structured agent communication. - Design secure agent systems with role-based access control and authentication mechanisms. - Develop scalable multi-agent workflows combining tools, memory, MCP, and retrieval. This program is ideal for developers, AI engineers, and technical professionals interested in building advanced agent systems and intelligent automation workflows. Prior experience with Python programming and basic AI concepts will help maxim