The Agent Service Bus: The Most Important Infrastructure Nobody Is Building
Everyone is talking about AI models and agent platforms. Almost nobody is talking about the infrastructure that makes agents actually work together. In this second article of Arion Research's "Future Enterprise" series, we examine the Agent Service Bus, the most strategically important layer in the enterprise AI stack and the one getting the least attention. We break down the five functions it must perform, assess where current protocols (A2A, MCP) fall short, and explore who will build the missing pieces.
The Model Context Protocol: Understanding Its Limits and Planning Your Agent Stack
The Model Context Protocol (MCP) received significant fanfare as a standardized way for AI agents to access tools and external systems. Anthropic's launch generated enthusiasm in the AI community, particularly among developers building local and experimental agentic systems. But as organizations move from proof-of-concept to production deployments, MCP's limitations are becoming apparent.
This isn't a story about MCP "failing" or being replaced overnight. Rather, MCP is settling into its actual role: one integration pattern among many, useful in specific contexts but insufficient as the primary fabric for enterprise agentic systems. Understanding where MCP fits (and where it doesn't) is essential for anyone building production-grade agent infrastructure.