AI assistants have gotten remarkably good at reasoning. What they still cannot do on their own is act — check your database, create a calendar event, query a live API, look up a record in your CRM, open a pull request. Their knowledge is frozen at a training cutoff, and they have no way to reach outside that boundary unless something bridges the gap.

Model Context Protocol (MCP) is that bridge.

The problem MCP solves

Before MCP, connecting an AI assistant to an external service meant writing a custom integration every time. A function definition, input schema, auth handling, error logic — and you needed to do all of that separately for each service and each AI model. Connect five services to three models and you have fifteen custom connectors to build and maintain.

IBM describes this as the "N×M integration challenge" — N models needing to connect to M external systems, each combination requiring its own implementation.…