Integrate AI into legacy systems using Model Context Protocol (MCP)

How can AI work with legacy systems—without costly overhauls?
In this episode, we break down Model Context Protocol (MCP): a communication layer that connects AI with your existing systems. You’ll hear not only what MCP can do, but also where its limits are and how to prepare your data before connecting it.

You’ll learn:

• Why most AI projects stall at proof of concept—and how MCP helps break that deadlock.

• What Model Context Protocol actually is and how it functions as a hub between AI and legacy systems.

• The limitations of MCP and what it cannot solve on its own.

• The business benefits of this integration model—from lower costs and risks to stronger data control.

• How rollout times shrink from weeks to days when MCP replaces brittle point-to-point integrations.

• Three practical ways to break data out of silos before plugging MCP in.

MCP transforms legacy systems from dead weight into an active resource—accessible, consistent, and ready for AI.

👉 Want to explore how this could work in your organization? Get in touch: inwedo.com/contact