Ever wanted to build a tool you could test and run directly in Cursor, with zero frontend, just TypeScript, and a sprinkle of MCP magic?

Let’s go from zero to “Hey, this runs inside Cursor!” in a few minutes using Model Context Protocol (MCP) and the official SDK.

lovestaco

Model Context Protocol: The Secret Sauce Behind Smart AI Tools

Athreya aka Maneshwar ・ Apr 9

#webdev #programming #beginners #ai

Setup

Start with a fresh project (or clone an existing one). The setup uses:

package.json overview:

{
  "name": "mcp-tools",
  "type": "module",
  "dependencies": {
    "@modelcontextprotocol/sdk": "^1.4.0",
    "zod": "^3.24.1"
  },
  "scripts": {
    "build": "pnpm build:all",
    "build:hello": "mkdir -p bin && bun build src/hello.ts --compile --minify --sourcemap --outfile bin/mcp-hello",
    "build:weather": "mkdir -p bin && bun build src/weather.ts --compile --minify --sourcemap --outfile bin/mcp-weather"
  }
}

Install dependencies:

pnpm install

Example Tool: Weather Alerts

Create your first tool in src/weather.ts:

import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";
import { z } from "zod";

// Create an MCP server instance
const server = new McpServer({
    name: "weather-tool",
    version: "1.0.0",
});

// Register a weather alerts tool
server.tool(
    "get_alerts",
    "Get weather alerts for a state",
    {
        state: z.string().min(2).max(2).describe("Two-letter state code (e.g. CA, NY)"),
    },
    async ({ state }) => {
        // In a real implementation, this would call a weather API
        // For this example, we'll just return mock data
        const mockAlerts = {
            "CA": ["Wildfire warning in Northern California", "Heat advisory in Southern California"],
            "NY": ["Flood warning in Western New York", "Thunderstorm watch in NYC metro area"],
            "FL": ["Hurricane watch along the coast", "Flood warning in South Florida"],
        };

        const alerts = (mockAlerts as Record<string, string[]>)[state] || ["No current alerts for this state"];

        return {
            content: [
                {
                    type: "text",
                    text: `Weather Alerts for ${state}:\n${alerts.map(alert => `- ${alert}`).join('\n')}`,
                },
            ],
        };
    }
);

// Start the server using stdio transport
async function main() {
    const transport = new StdioServerTransport();
    await server.connect(transport);
    console.error("Weather MCP Tool running on stdio");
}

main().catch((error) => {
    console.error("Fatal error:", error);
    process.exit(1);
});

This exmaple has hardcoded data mockAlerts. You can use your API here.

Build It

To compile the tool into a native executable using Bun:

pnpm build:weather

Check the output:

./bin/mcp-weather

You should see logs like:

Weather MCP Tool running on stdio

Image description

Setup for cursor

  1. Open Cursor Settings (Ctrl+Shift+j)
  2. Select Features
  3. Click on Add new MCP server
  4. Give the full path of the binary Ex: /home/lovestaco/pers/mcp-example-weather-hello-blog/bin/mcp-weather

Image description

How to run your MCP tool in Cursor:

  1. Go to Cursor's chat panel.
  2. Ask your query

Image description

Image description

Hot Reload (Optional)

For faster dev loops:

pnpm watch:weather

Now any change to src/weather.ts will rebuild the binary automatically.

TL;DR Commands 

pnpm build         # build all tools
pnpm build:weather # build weather tool

# Run the binary
./bin/mcp-weather

# Watch mode (auto-rebuild)
pnpm watch:weather

Wrapping Up

With just a bit of TypeScript and MCP SDK, you can turn any script or tool into something Cursor can interact with directly.

It’s like CLI meets LLM tooling — with schema validation, zero boilerplate, and instant feedback inside your editor.

Want to build more tools? Just add new .ts files, register new server.tool() calls, and compile.

Cursor will treat them like first-class AI copilots.

Full source code available here: lovestaco/mcp-example-weather-hello-blog

I picked this up while exploring courses on Egghead. Checkout egghead's other courses on MCP [ 1, 2, 3]

I’ve been actively working on a super-convenient tool called LiveAPI.

LiveAPI helps you get all your backend APIs documented in a few minutes

With LiveAPI, you can quickly generate interactive API documentation that allows users to execute APIs directly from the browser.

image

If you’re tired of manually creating docs for your APIs, this tool might just make your life easier.