本文围绕大语言模型（LLMs）智能应用中的工具与数据接入问题，系统介绍了两种主流方案：基于 Agent + Function Call 的动态调度机制与基于 MCP（Model Context Protocol）的标准化接入框架。通过梳理各自的工作原理、应用流程及典型实践，分析了不同场景下的适用性选择。

快速导读：前Meta收购公司Manus的后端技术负责人，在构建AI Agent两年后得出惊人结论：别再用复杂的Function Calling了。LLM的原生语言其实是诞生于50年前的Unix命令行。本文揭示了为什么一个简单的`run(command ...

本文旨在为初学者揭开MCP和Function Calling的神秘面纱，以清晰易懂的方式澄清二者之间的关系。我们将基于当前主流的学习趋势，解释它们为何对AI的未来发展至关重要。要厘清它们的关系，我们首先需要独立地理解每一个概念的定义和作用。 引言：为什么我们都 ...

Function calling is a feature that allows you to describe specific functions to ChatGPT models within an API call. The model, in turn, intelligently decides whether to generate a JSON object, ...

The introduction of Google’s Gemini API marks a significant step forward for those who develop software and create digital content. The API allows you to harness the power of Google’s latest ...

As OpenAI has gained more popularity than ever thanks to the launch of ChatGPT last fall, its application programming interface (API) has also become a sought-after tool for developers. Different ...

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