[Purpose/Significance] To address limited intelligence, passive service models, and inefficient resource integration in library reference services, this study explores intelligent transformation pathways enabled by the Model Context Protocol (MCP). The lack of standardized interaction between large language models (LLMs) and heterogeneous library systems restricts the effective use of resources and professional services. By connecting LLMs with external resources and authorized tools through a unified protocol, MCP can help establish proactive, precise, personalized, and context-aware services and support smart library development. [Method/Process] Considering MCP’s characteristics and compatibility with library operations, this study constructs a four-layer interaction model of “Resource-MCP-LLM-User” and proposes an architecture comprising the MCP server, MCP protocol, foundational LLM, and user layers. The MCP server layer encapsulates library databases, knowledge bases, and tools as standardized resources and callable functions. The protocol layer supports capability discovery, permission control, and data exchange. The foundational LLM layer performs intent recognition, task planning, tool selection, information synthesis, and response generation, while the user layer supports natural-language interaction. Through protocol parsing, tool encapsulation, context management, and task coordination, the architecture enables LLMs to invoke heterogeneous resources and integrate information into coherent knowledge services. Service rules, domain knowledge, and access permissions can be incorporated to preserve librarians’ professional role. [Result/Conclusion] The findings indicate that MCP can improve the connectivity, interoperability, flexibility, and scalability of intelligent reference services. Through standardized and controlled interfaces, libraries can expose existing resources and capabilities to LLMs and expand services according to their collections, infrastructure, expertise, and user needs. MCP therefore supports a transition from passive question answering to proactive need identification, contextual interaction, and knowledge-based assistance. The proposed model provides a scalable theoretical framework and feasible technical guidance for library transformation, promotes the integration of resources, intelligent technologies, and professional services, and advances public cultural services toward proactive, personalized, and knowledge-driven development.
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