What problem does MCP solve?
Before MCP, connecting an AI assistant to a business system meant custom integration work for every capability, in every assistant, one at a time. Each new action was another development project.
MCP inverts that. The business system runs an MCP server that publishes a list of tools — each with a name, a description and a typed input. Any MCP-capable AI can read that list and use it. Add a tool on the server and every connected assistant can use it immediately.
How does an MCP call work?
- The AI connects to the MCP server and requests the tool list.
- The server returns tools with descriptions and input schemas.
- The AI chooses a tool and supplies validated arguments.
- The server authenticates the caller and enforces permissions.
- The server executes, writes an audit record, and returns a result.
Why does this change what AI can be?
It moves AI from producing descriptions of work to performing work. The same request that previously ended with 'here is a draft you can copy' can end with a contract created, sent for signature and logged.
The intelligence is not new. The permission to act is.