As AI agents transition from pilots to production systems, enterprises are rapidly adopting the open source Model Context Protocol (MCP) to connect models with tools, data, and services. But this flexibility introduces a new challenge: MCP server sprawl. Proliferating endpoints, inconsistent trust models, weak identity controls, and unclear governance can quickly create operational and security risk. This session explains what MCP is, why its adoption is accelerating, and where architectural pitfalls emerge at scale. Developers will learn key design principles for secure deployment, including authentication patterns, authorization boundaries, observability, lifecycle management, and policy enforcement. Attendees will leave with a practical mental model for building MCP integrations that remain composable, governable, and production-ready as ecosystems evolve.