If the big language model solves the problem of "understanding and generation", then for agents to truly land, they also need to solve the problem of "connection and action" - how the model can securely and stably call external tools and data. MCP (Model Context Protocol) is a rapidly popular standard solution in this context.
MCP was open sourced by Anthropic in November 2024. Its design concept is to establish a unified interface specification between mainstream AI applications and external tools: through a three-tier architecture of Host, Client, and Server, the file system, database, development tools, web services, and other capabilities are encapsulated into "tools" that can be called by the model. Prior to this, each application had to write a private integration code for each tool, and MCP's goal was to standardize this work.
This standard has been rapidly promoted in 2025: major manufacturers such as OpenAI and Google have announced support for MCP in their products, and many large model manufacturers and developer tools in China have also followed suit. For developers, the direct benefit of MCP is a reduction in integration costs - writing a tool package once can be reused by multiple AI applications that support MCP.
From practical use, the most typical scenarios of MCP include: code assistants reading local repositories and executing builds, agents querying enterprise knowledge bases and databases, automated processes calling third-party SaaS services, etc. It enables agents to move from "only able to talk" to "operable", which is also one of the fundamental capabilities for multi-agent collaboration and complex task automation.
Of course, MCP is not without challenges. Firstly, there is the security boundary: if the tool permissions are too large or the authentication is not strict, it may be exploited by malicious prompt words; Secondly, the protocol is still evolving, and the compatibility of different implementations requires time for adaptation; Finally, the quality of the tool ecosystem varies greatly, and how to select trustworthy and stable tool servers will become the core competitiveness of the Agent platform.
Overall, the value of MCP lies not in any technological breakthrough, but in pushing the concept of "AI connecting the world" from a fragmented private solution to a public standard. For developers and enterprises, now is the appropriate time to evaluate and pilot MCP on a small scale.
[Reference source] Comprehensive compilation of industry information publicly released.