Speaker
Description
INSPIREHEP is evolving toward a new search and discovery platform that combines AI assisted retrieval with a unified service for metadata and content processing. This contribution presents the design and planned deployment of two core components. The first is an AI based retrieval pipeline that enriches records with embeddings, improves ranking behaviour, and supports natural language queries. The second is the MCP server, a central service for metadata transformation, content normalization, and cross service coordination within the INSPIREHEP ecosystem.
The architecture introduces a single service that centralises the RAG pipeline and the MCP functions that connect records, metadata, and tooling across the platform. It improves discoverability, enables natural language queries, and provides a consistent entry point for INSPIREHEP services and collaborators to access the same capabilities with minimal integration effort.
This work strengthens the long term maintainability of the INSPIRE software ecosystem and prepares the platform for upcoming AI driven developments.