Why the Virtual World of Web3 Needs MCP: The End of Prompt-Only AI
In today’s AI landscape, many interactions still rely on large language models (LLMs) in a very basic format: prompt → output → repeat. While this pattern is sufficient for chatbots and demo apps, it falls far short when it comes to building rich, complex virtual societies.
Key limitations of conventional LLMs:
No long-term memory
Not modular or contextual
Cannot coordinate between agents
However, virtual societies in Web3 like AIVille 2.0 demand more. They require AI that can:
Remember past interactions
Understand roles and rules
Coordinate with agents and humans
Execute tasks based on protocols, not just free-form text
The solution? The Model Context Protocol (MCP) — a sophisticated orchestration system that enables AI agents in AIVille 2.0 to act, think, and collaborate contextually.
With MCP, agents don’t just respond — they perform roles.