What Is MCP?
Model Context Protocol (MCP) is an open standard created by Anthropic that defines how AI models interact with external tools, data sources, and services. Think of it as USB-C for AI — one universal connector.
Why MCP Matters
Before MCP, every AI integration was custom:
- OpenAI had function calling
- LangChain had tool abstractions
- Every agent framework had its own format
MCP unified this. One protocol, every model, every tool.
How It Works
{
"name": "search_codebase",
"description": "Search for code patterns in the repository",
"parameters": {
"query": { "type": "string" },
"file_type": { "type": "string", "optional": true }
}
}
MCP servers expose tools. MCP clients (like Claude) consume them. The protocol handles:
- Discovery — What tools are available?
- Invocation — Call a tool with parameters
- Results — Structured responses back to the model
The Ecosystem
300K+ GitHub stars. 2,000+ MCP servers available:
- File systems — Read/write local files
- Databases — Query PostgreSQL, SQLite, MongoDB
- APIs — GitHub, Slack, Jira, Linear
- Browsers — Web scraping and automation
- Custom tools — Build anything
Building Your Own MCP Server
import { McpServer } from '@anthropic-ai/mcp';
const server = new McpServer({
name: 'my-tool',
version: '1.0.0',
});
server.tool('greet', { name: 'string' }, async ({ name }) => {
return { message: `Hello, ${name}!` };
});
server.start();
The Future
MCP is becoming the default integration layer for AI. If you're building tools for AI, build an MCP server. If you're building with AI, look for MCP-compatible tools first.
The protocol is open, the ecosystem is thriving, and the standard is here to stay.
