What is MCP? A Complete Guide to the Model Context Protocol
The Model Context Protocol (MCP) is an open standard that connects AI assistants to external tools and data sources. Think of it as USB-C for AI — a universal protocol that lets any AI client talk to any backend service.
Why MCP Matters
Before MCP, connecting an AI assistant to an API required custom integration code. Every tool had its own plugin format, authentication scheme, and configuration approach. MCP standardizes this into a single protocol.
The ecosystem has grown to over 12,000 MCP servers, with SDK downloads exceeding 97 million. Major AI clients including Claude Desktop, Cursor, Cline, and Continue.dev all support MCP natively.
How MCP Works
MCP has three core components:
- Host — The AI application (Claude Desktop, Cursor) that requests tools and data
- Client — A protocol client that maintains a connection to an MCP server
- Server — A lightweight server that exposes tools, resources, and prompts through the protocol
When you ask your AI assistant to "look up a GitHub issue" or "query the database," the assistant uses MCP to communicate with the appropriate server, which handles the actual API call.
MCP vs OpenAPI
OpenAPI describes what an HTTP API can do. MCP describes what an AI assistant can do with external tools. They're complementary: OpenAPI specs can be converted to MCP configurations, which is exactly what MCP-Bridge does.
Getting Started
To use MCP, you need an MCP-compatible client and one or more MCP server configurations. You can: