MCP is short for 'Model Context Protocol', which means model context protocol. It is the core technology framework of AIVille 2.0, responsible for coordinating large language models (LLMs) and autonomous agents, endowing them with persistent contextual awareness and modular task execution.
Has a three-layer structure:
Context Layer: Manages the AI's current state, memory, observations, and input streams. It allows the AI to build structured, hierarchical world models.
Protocol Layer: This layer defines the task scheme, expressed in a machine-readable contract form, describing what the AI should do, what inputs are needed, and under what constraints it operates.
Execution Layer: The runtime layer that maps the protocol contract to the actual system capabilities.
MCP manages dynamic context, defines task schemes, and enables asynchronous orchestration, allowing roles like Lucas or Selena to interact in real-time based on memory and tasks, breaking through the limitations of traditional AI.
eMCP: Enhanced Protocol Cognition
AIVille also proposes the research direction of eMCP (Enhanced Model Context Protocol), which is the evolution of MCP and will support:
Introducing cross-agent shared memory
Multi-turn strategy alignment
Long-term task support
Trust-based protocol arbitration
eMCP lays the foundation for building a scalable AI society and promotes the evolution of consensus among AI roles.
Conclusion
MCP is not just a technical framework, but a brand new AI system paradigm. Through its three-layer structure and the innovative evolution of eMCP, AIVille 2.0 not only reshapes the cognition and collaboration methods of agents but also opens up vast prospects for AI-driven governance and narratives. This paradigm will lead the development of an AI intelligent society, unlocking infinite possibilities.