Abstract Summary
PyTerrier provides a declarative framework for building and experimenting with information retrieval (IR) pipelines. In this demonstration, we highlight several recent higher-level pipeline operations that improve their ability to be programmatically inspected, visualized, and integrated with other tools (via the Model Context Protocol, MCP). These capabilities aim to make it easier for researchers, students, and AI agents to understand and use a wide array of IR pipelines.
