Building AI Agents: Workflow Automation with Claude MCP

As AI moves from simple chat interfaces to autonomous entities, understanding how to build and manage agents is becoming a vital skill. This course provides a clear path for anyone looking to bridge the gap between large language models and practical, automated workflows. You will transform from a casual AI user into someone who can conceptualize and structure agentic systems that interact with external tools and data sources. By focusing on the Model Context Protocol (MCP), you will learn how to standardize the way AI models access the information they need to perform complex tasks independently. What you'll learn: - Understand the core architecture and logic of autonomous AI agents - Learn the Model Context Protocol (MCP) to securely connect models with local and remote data - Configure tool-use patterns that allow agents to execute specific actions within a workflow - Design multi-step automation sequences that handle data retrieval and processing - Apply modern security practices to ensure agent reliability and data privacy - Practice structuring agent prompts to improve decision-making and task execution The course begins with essential terminology and the conceptual framework of agentic behavior before moving into the technical mechanics of MCP and workflow design. You will progress through written explanations and logic-based exercises designed to solidify your understanding of modern AI automation. This course is designed for beginners interested in the future of AI productivity; no previous programming or AI development experience is required. Start building more capable and connected AI systems today.