Enhancing Dspace with Large Language Models: Designing an Integration Framework Using the Model Context Protocol

This study aims to integrate Natural Language Processing (NLP) services within the DSpace-based repositories by using Model Context Protocol (MCP), a novel framework that promotes secured and seamless integration between LLM and external tools. This research study deployed Claude Sonnet as a front-end LLM and DSpace 9.1 as back-end digital repository software and
connected them by using the MCP server to enable the natural language-based retrieval. This study highlights how MCP may allow context-aware NLP services to enhance metadata-driven retrieval and semantic search, as well as the multilingual information retrieval. It highlights the advantages of natural language-based retrieval and also identifies the limitations of this approach. This study reports developing a working prototype for natural language-based retrieval of DSpace and discusses
the feasibility of this approach in real-world digital library settings, with a focus on large-scale national initiatives such as the National Digital Library of India (NDLI).