Data engineering involves significant effort, often characterized by managing complex tools and systems to ensure smooth data operations, with tasks like checking pipelines frequently leading to extensive troubleshooting. To alleviate this burden, the Model Context Protocol (MCP) offers a framework for connecting AI applications to external systems, enabling assistants like Claude and ChatGPT to interact with tools such as dbt and Prefect. With MCP, users can leverage AI to perform tasks such as identifying pipeline issues, suggesting fixes, and managing deployments without needing in-depth knowledge of the underlying systems. The Prefect MCP server allows AI clients to query system status, analyze flow patterns, and execute commands, simplifying processes like canceling delayed runs or debugging failures. This beta release, available through the MCP registry and GitHub, invites user feedback and encourages contributions to enhance its functionality and integration capabilities.