This article provides an in-depth analysis of the Model Context Protocol (MCP), its core architecture, communication mechanisms, and implementation methods, detailing how this standardized protocol enables seamless integration between LLMs and external tools, laying the foundation for building scalable, interoperable AI ecosystems.
This article provides an in-depth analysis of LLM tool calling's core principles, technical implementation, code examples, and best practices, detailing how this mechanism enables large language models to break knowledge boundaries and interact with the external world.