一个能自适应多种交互方式的智能体架构，可动态配置工具与记忆系统。
STEM Agent: A Self-Adapting, Tool-Enabled, Extensible Architecture for Multi-Protocol AI Agent Systems
- 通过模块化设计让智能体核心按需分化为不同功能组件。
- 支持五种协议统一接入，用户行为分析覆盖20+维度。
- 适合需要跨平台协作、持续学习的复杂智能体应用。
当前AI智能体框架过早固定交互协议、工具集成方式和用户模型，限制了在多样交互范式中的部署。为此，我们提出STEM Agent（自适应、工具增强、可扩展、多智能体），其架构受生物多能性启发，未分化的智能体核心可分化为专用协议处理器、工具绑定和记忆子系统，组合成完整AI系统。该框架统一五种互操作协议（A2A、AG-UI、A2UI、UCP、AP2）通过单一网关，引入呼叫者分析器（Caller Profiler），持续学习超过二十个行为维度的用户偏好；通过模型上下文协议（MCP）外部化所有领域能力；实现类细胞分化机制的技能获取系统，重复交互模式经成熟生命周期结晶为可复用技能。记忆系统包含情景删减、语义去重和模式提取等整合机制，支持持续交互下的次线性增长。413项测试验证各层协议处理器行为与组件集成，总耗时不足三秒。
原文摘要 · Abstract (English)
Current AI agent frameworks commit early to a single interaction protocol, a fixed tool integration strategy, and static user models, limiting their deployment across diverse interaction paradigms. To address these constraints, we introduce STEM Agent (Self-adapting, Tool-enabled, Extensible, Multi-agent), a modular architecture inspired by biological pluripotency in which an undifferentiated agent core differentiates into specialized protocol handlers, tool bindings, and memory subsystems that compose into a fully functioning AI system. The framework unifies five interoperability protocols (A2A, AG-UI, A2UI, UCP, and AP2) behind a single gateway, introduces a Caller Profiler that continuously learns user preferences across more than twenty behavioral dimensions, externalizes all domain capabilities through the Model Context Protocol (MCP), and implements a biologically inspired skills acquisition system in which recurring interaction patterns crystallize into reusable agent skills through a maturation lifecycle analogous to cell differentiation. Complementing these capabilities, the memory system incorporates consolidation mechanisms, including episodic pruning, semantic deduplication, and pattern extraction, designed for sub-linear growth under sustained interaction. A comprehensive 413-test suite validates protocol handler behavior and component integration across all five architectural layers, completing in under three seconds.
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