I’ll keep this short because the headline writes itself: the protocol war for AI agent connectivity never happened. Anthropic shipped the Model Context Protocol. OpenAI adopted it. Google adopted it. Microsoft adopted it. The industry converged on a single standard faster than anyone predicted.
MCP won. Congratulations. Now let’s talk about why that was the easy part.
The USB-C Analogy Is Perfect (and Incomplete)
People love the “MCP is USB-C for AI” comparison, and it’s apt. Before USB-C, every device had its own cable. Before MCP, every AI integration was a custom snowflake. MCP gives you a universal connector.
But USB-C didn’t solve the hard problems of peripheral computing. It solved the connector problem. You still needed drivers, power management, bandwidth negotiation, and device authentication. The cable was necessary but nowhere near sufficient.
MCP is the cable. The hard part is everything else.
What Happens at 200 MCP Servers
Here’s where things get real. Most AI agent deployments today connect to a handful of tools. Your agent talks to Slack, GitHub, maybe a database. Three or four MCP servers. Manageable.
I’ve spent my career building systems that integrate with lots of other systems. At Xively, our IoT platform had to talk to thousands of different device types, each with their own protocols, data formats, and failure modes. At Drift, we built a conversational platform that integrated with dozens of sales and marketing tools. The pattern is always the same: connecting to one thing is easy. Connecting to many things surfaces a whole category of problems that didn’t exist at small scale.
When your AI agent has access to forty tools, three problems become existential:
Permission scoping. Which tools can the agent use in which context? An agent helping with code review shouldn’t have access to the HR system. An agent drafting a customer email shouldn’t be able to execute database queries. The permission model needs to be granular, contextual, and auditable. MCP doesn’t solve this. You do.
Context flooding. Every MCP server exposes tool descriptions, schemas, and capabilities. Forty servers means a lot of context competing for attention in the model’s window. The agent needs to understand which tools are relevant right now without being overwhelmed by the full catalog. This is a retrieval and routing problem that gets harder as you add integrations.
Tool selection reliability. With four tools, the model picks the right one most of the time. With forty, misrouting becomes a real failure mode. The agent calls the wrong tool, gets back unexpected data, and either halts or proceeds with bad information. You need a selection layer that’s more sophisticated than “put all the tool descriptions in the prompt and hope for the best.”
The Integration Layer Is the Product
I’ve seen this movie before. The exciting technology gets all the attention. The integration layer that makes it work in production gets none. And then the integration layer turns out to be where all the real engineering lives.
REST APIs were exciting. API gateways, rate limiting, authentication, and observability were the actual product. Microservices were exciting. Service meshes, circuit breakers, distributed tracing, and deployment orchestration were the actual product.
MCP is exciting. The permission models, routing logic, context management, and audit infrastructure built on top of it? That’s where the value will compound.
What This Looks Like in Practice
At Vestmark, we’ve been building around this principle. Every MCP connection goes through authentication via Okta OIDC. Every tool invocation is logged. Every agent operates within a defined permission boundary. The routing layer considers what the agent wants to do and whether it should be allowed to do it in the current context.
This work doesn’t make for a good demo. But it’s the difference between an AI toy and an AI product you can deploy in an environment where mistakes have consequences.
The protocol war is over. The integration war is just getting started. That’s where the real builders will separate themselves.