An API is how programs talk to your system. MCP is how AI assistants discover and use what your system can do. An MCP server usually calls your API under the hood.
Why not give the model the API directly?
- Discovery. MCP clients ask the server which tools exist and what they need. No custom integration per AI app.
- Shape. APIs are built for developers. Tools are built for a model: fewer, clearer, with descriptions it can follow.
- Control. The MCP server is where you enforce permissions, limits, confirmation and logging, in one place.
- Portability. One server works across Claude, ChatGPT, Cursor and agent frameworks.
A simple rule
Keep your API as it is. Put a thin, well-designed MCP server in front of the parts of it your team wants to use through AI. See MCP for internal APIs.