Anatomy of an AI Agent: How MCP Connects Agents to Your Business Systems
In our previous posts, we broke down how system prompts govern agent behavior and how the tool-calling loop actually works. Both of those pieces assumed something that, in practice, is the hardest part of building a production AI agent: the agent can actually talk to your business systems.
That’s the integration problem. And until recently, it was brutal.
If you wanted an AI agent that could look up customer orders, check inventory, update a CRM record, and send a follow-up email, you needed four separate integrations — each with its own authentication flow, data format, error handling, and maintenance burden. Five AI platforms connecting to twenty business tools meant a hundred integration projects. Every new tool or model multiplied the work.