This podcast introduces the Model Context Protocol (MCP), a standardized interface designed for AI models to interact with external tools and resources. The authors comprehensively describe MCP's architecture, including its core components like the host, client, and server, along with the lifecycle of MCP servers through creation, operation, and update phases. A key focus of the paper is the analysis of security and privacy risks associated with each stage of the MCP server lifecycle, offering potential mitigation strategies. The work also examines the current adoption landscape of MCP across various industries and highlights community-driven initiatives and supporting tools. Finally, this podcast discusses the broader implications of MCP, outlines future research directions, and provides recommendations for stakeholders to ensure its secure and sustainable development within the evolving AI ecosystem.