This hands-on workshop shows you how to build smarter AI agents: ones that don’t lose context. You’ll use Neo4j’s Model Context Protocol (MCP) to give your agents persistent, graph-based memory, allowing for richer, multi-turn interactions and intelligent behavior grounded in your data. You’ll walk through the full agent-building process: from setting up a knowledge graph, to integrating GraphRAG for multi-hop reasoning, and deploying an agent with contextual memory that evolves over time. By the end of the session, you’ll have a working, production-ready AI agent you can extend for your own use cases.