Learn to build production-grade MCP servers that connect AI to your data. Master resources, tools, and prompts with the open standard revolutionizing AI integration.

TL;DR: MCP (Model Context Protocol) is the open standard connecting AI to your data. This workshop teaches you to build production-grade MCP servers with resources, tools, and prompts.
Before MCP, every AI integration was custom. Now there's a standard:
| Before MCP | After MCP |
|---|---|
| Custom integrations | Standard protocol |
| One-off solutions | Reusable servers |
| Security per integration | Built-in security |
| Vendor lock-in | Universal compatibility |
MCP lets AI models connect to your data through three primitives:
Data exposed to the model:
Actions the model can take:
Reusable templates:
Here's the basic structure:
import { Server } from "@modelcontextprotocol/sdk/server/index.js";
const server = new Server({
name: "my-server",
version: "1.0.0",
});
// Implement resources
server.setRequestHandler("resources/list", async () => ({
resources: [
{
uri: "notes://all",
name: "All Notes",
mimeType: "application/json",
},
],
}));
// Implement tools
server.setRequestHandler("tools/list", async () => ({
tools: [
{
name: "create_note",
description: "Create a new note",
inputSchema: {
type: "object",
properties: {
title: { type: "string" },
content: { type: "string" },
},
},
},
],
}));
The ecosystem is growing fast:
| Server | Purpose |
|---|---|
| PostgreSQL | Query databases naturally |
| GitHub | Manage repos and PRs |
| Slack | Send messages, manage channels |
| Filesystem | Read and write files |
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