Model Context Protocol (MCP)

What is MCP?

MCP (Model Context Protocol) is an open protocol that standardizes how AI models access external tools, file systems, databases, and APIs. Designed and released by Anthropic, MCP can be implemented by anyone to plug into their own AI applications.

Think of MCP as USB-C for the AI world. Just as a single USB-C standard lets you connect countless devices, any MCP client can talk to any MCP server — so any AI model can plug into any tool, as long as both speak the same protocol.

How Does It Work?

MCP uses a client-server architecture:

• MCP Server — exposes a specific tool or data source (e.g., a Git repository reader, a database query service).
• MCP Client — the AI assistant side: Claude Desktop, Claude Code, VS Code extensions, and more.
• The two communicate via standardized JSON-RPC messages. Servers offer tools, resources, and prompts that the model can invoke as capabilities.

Build an MCP server once, and multiple AI tools can reuse it. Conversely, an AI tool gains many new capabilities just by adding one more server — no custom integration code per tool.

Why Does It Matter?

Before MCP, every AI agent invented its own way to connect tools, forcing teams to reimplement the same integrations over and over. MCP removes that fragmentation with a shared standard, lowering integration cost across the entire ecosystem and letting AI assistants consistently reach internal company systems, personal files, and third-party SaaS. As agentic AI moves into real workflows, a standard interface like this becomes essential — and MCP is emerging as the leading candidate.