MCP Servers Explained
What MCP servers are, how they work, and how to build your own in 5 minutes.
MCP Servers Explained
MCP (Model Context Protocol) lets AI tools connect to external services. Think of it as USB ports for AI -- plug in any tool and your AI agent can use it.
How it works
- An MCP server exposes tools (functions the AI can call)
- Your AI client (Claude Code, Cursor, etc.) connects to the server
- The AI can now call those tools as part of its workflow
Example: DevDigest MCP Server
The dd mcp command starts an MCP server with these tools:
init_project-- Scaffold a new projectlist_commands-- Show available commands
Add to Claude Code
In your project's .mcp.json:
{
"mcpServers": {
"devdigest": {
"command": "dd",
"args": ["mcp"]
}
}
}
Build your own MCP server
import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";
import { z } from "zod";
const server = new McpServer({
name: "my-server",
version: "1.0.0",
});
server.tool(
"hello",
"Say hello",
{ name: z.string() },
async ({ name }) => ({
content: [{ type: "text", text: `Hello, ${name}!` }],
})
);
const transport = new StdioServerTransport();
await server.connect(transport);
Agent prompt
Copy this to give your AI agent MCP context:
This project uses MCP servers for external tool integration. Check .mcp.json for available servers. You can call MCP tools directly -- they appear as regular tools in your tool list.
Technical content at the intersection of AI and development. Building with AI agents, Claude Code, and modern dev tools - then showing you exactly how it works.
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