What is the Model Context Protocol?
The Model Context Protocol (MCP) is an open standard designed to provide a universal, secure architecture for AI models to connect to external data sources. It standardizes how AI applications communicate with local files, enterprise databases, and remote APIs.
How does it work?
MCP uses a strict client-server architecture:
- MCP Host: The AI application (like an IDE or a chat interface) where the model operates.
- MCP Client: Code inside the host that initiates connections.
- MCP Server: A lightweight, standalone program that bridges the gap to a specific data source. The server exposes Resources (data), Prompts (templates), and Tools (executable actions) to the client in a standardized JSON format.
What is it commonly confused with?
MCP is not an AI model, nor is it a marketplace for apps. It is also not an automated security system; it does not magically make every connected tool safe. Security still relies on the developer restricting what the MCP server is allowed to do on the host machine.
Why does it matter?
Before MCP, every AI application had to build custom API integrations for every possible data source. MCP acts as the "USB-C for AI," allowing developers to write a data integration once and use it universally across any AI model or application that supports the protocol.