
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).
Large Language Model (LLM), Information Retrieval, Natural Language Processing (NLP), NDLI, Model Context Protocol (MCP), Claude, DSpace
Large Language Model (LLM), Information Retrieval, Natural Language Processing (NLP), NDLI, Model Context Protocol (MCP), Claude, DSpace
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