Core Insights - The article discusses the paradigm shift in AI large model application development from "single Q&A" to "autonomous task execution" by 2025, emphasizing the importance of the Model Context Protocol (MCP) as a key infrastructure for enterprise-level AI applications [2][4]. Group 1: MCP Protocol - The MCP protocol, launched by Anthropic in November 2024, aims to address the fragmentation issue in AI model interactions with external tools, functioning like a universal socket for AI tool calls [2]. - The technical architecture of MCP employs a client-server model, allowing developers to encapsulate tools as MCP servers, enabling multiple AI models to utilize them without custom integration [2]. Group 2: Intelligent Agent Development - The proliferation of the MCP protocol is driving intelligent agent development towards "platform-level collaboration," allowing for comprehensive solutions that cover entire business processes by combining multiple tool servers [3]. - Typical use cases involve AI models acting as "smart assistants" that understand user intent and select appropriate tools, while servers provide data or tool services through standardized interfaces [3]. Group 3: Ecosystem Building - The promotion of the MCP protocol relies on collaborative efforts within the industry, exemplified by the establishment of the AI Agent Foundation (AAIF) in December 2025, which includes major tech companies and hardware manufacturers [4]. - Lenovo's "AI Factory" solution provides full-stack computing support for MCP intelligent agents, enabling automation in production processes and improving product quality rates to 99.2% [4]. Group 4: Future Outlook - As the MCP protocol becomes more widespread, AI intelligent agents are transitioning from specialized fields to the mass market, with low-code development platforms integrating MCP tools for rapid application development [4][5]. - Future applications of intelligent agents are expected to extend into IoT and edge computing, with capabilities such as real-time equipment analysis and automatic environmental adjustments in smart homes [5]. Group 5: Practical Applications - Companies are leveraging MCP for various applications, such as creating "smart office assistants" that streamline onboarding processes, reducing training time from 2 weeks to 3 days [6]. - In healthcare, intelligent agents are enhancing diagnostic accuracy by 22% through integration with electronic medical records and clinical decision support tools [6]. - Financial institutions are utilizing MCP to build real-time risk control systems that achieve a fraud transaction interception rate of 99.97% [6].