MCP Is a Great Start — But Multi-Agent Production Needs More

The Model Context Protocol has transformed how we connect AI to tools. But connecting agents to tools is only half the battle — connecting agents to each other is where the real challenge begins. The Article That Sparked This I recently read @anthonymax's excellent article "I Discovered An Enterprise MCP Gateway" and it resonated deeply with challenges I've been solving in production. This post highlights exactly what makes MCP powerful. Where I want to extend the conversation is: what happens when you have 3, 5, or 10 MCP-powered agents all sharing context? The Core Problem: State Coordination Here's what most multi-agent discussions miss: the frameworks are great at individual agent capabilities. LangChain gives you chains, AutoGen gives you conversations, CrewAI gives you roles. But when these agents need to share state — that's where things silently break. Timeline of a Production Bug: 0ms: Agent A reads shared context (version: 1) 5ms: Agent B reads shared context (version: 1) 10m