How does it work?
An AI model doesn't know your software, and it shouldn't just be let loose in it either. MCP solves that with a fixed agreement between two sides:
- The MCP server: a piece of software that exposes your system (or data) as a set of clear "tools", for example "find a customer" or "create an invoice".
- The AI (the client): asks that server which tools exist, and calls them when needed.
- The server executes: it performs the actual action in your system (with the right permissions and authentication, safely on the server side) and returns the result.
Without MCP, every connection between AI and software is custom work. With MCP, they speak the same language.
What is it for?
MCP is the way to let an AI work with the tools and data you already have, without building a separate connection for every combination:
- Connecting AI to your own systems: your ERP, accounting, CRM or company brain, so an assistant works with your real data.
- Letting it take actions: not just answering, but also doing something (creating a task, drafting a document, updating a record).
- The same connection for multiple AIs: Claude, Microsoft Copilot and tools that run via the command line (like Claude Code) can all plug into the same MCP server. You build the bridge once.
Why does it matter?
In the past you had to build a separate, often fragile integration for every AI tool and every system. MCP turns that into a common language: one standard you can reuse. That means less custom work, and above all: you're not locked into one AI vendor. A better model or a different tool comes along tomorrow? It plugs into the same MCP server.
Important to know: MCP is the plug, not the installation. Someone still has to build and maintain the MCP server, make the real connection to your systems (including those without a ready-made API), and set up security and permissions properly.
Related terms
- RAG: letting an AI answer based on your own sources; MCP is one way to unlock those sources and tools.
- EU hosting and zero retention: where your data is processed and whether it's reused, exactly the question that counts once AI is connected to your systems.
- Vector store: a common source you make available to an AI through a connection.
