MCP Sample Agent Tutorial
A Model Context Protocol (MCP) server that exposes tools, resources, and prompts for users and todos. Supports both stdio (local) and Streamable HTTP (cloud-ready) transports. This tutorial explains the project structure, how tools, resources, and prompts are built, and how to integrate with Cursor.
Prerequisites
- Node.js 18+
- npm or pnpm
Quick Start
npm install
npm run dev # Run the MCP server (Streamable HTTP on port 3000)
npm run inspect # Test in MCP Inspector
---
Project Structure
tc_mcp_III/
├── src/
│ ├── index.ts # Entry point: Express + Streamable HTTP transport
│ ├── server.ts # MCP server factory (createMCPServer)
│ ├── entities/
│ │ ├── user.entity.ts # Zod schemas and types for users
│ │ └── todo.entity.ts # Zod schemas and types for todos
│ ├── users/
│ │ └── userHandler.ts # Business logic: create, fetch users
│ ├── tools/
│ │ └── users/
│ │ ├── createUserTool.ts # MCP tool: create-user
│ │ └── fetchUsersTool.ts # MCP tool: fetch-users
│ ├── resources/
│ │ ├── users/
│ │ │ └── usersResources.ts # MCP resource: users (read-only)
│ │ └── todo/
│ │ ├── todoResources.ts # MCP resources: todos, single-todo (template)
│ │ └── todoHandler.ts # Fetches todos from dummyjson.com
│ └── prompts/
│ └── todos/
│ └── todosPrompts.ts # MCP prompt: fetch-todo-item
├── users.json # JSON "database" for users
├── .cursor/
│ └── mcp.json # Cursor MCP configuration
├── package.json
└── tsconfig.json
Layer Responsibilities
| Layer | Purpose | |-------|---------| | index.ts | Bootstraps Express, creates server per request, connects Streamable HTTP transport | | server.ts | Factory createMCPServer() for stateless per-request servers | | entities/ | Shared schemas (Zod) and TypeScript types | | users/ | Domain logic (CRUD) independent of MCP | | tools/ | MCP tool definitions: wire schema + handler via registerXxx(server) | | resources/ | MCP resource definitions: read-only data exposed via URI | | prompts/ | MCP prompt templates for AI interactions |
---
Transport: Streamable HTTP
The server uses Streamable HTTP transport, making it suitable for cloud deployment (e.g., GCP Cloud Run). Each HTTP request gets a fresh MCP server instance (stateless pattern).
How It Works
- Express app listens on
PORT(default 3000) - All MCP traffic goes to the
/mcpendpoint - For each request: create server → register tools/resources/prompts → connect transport → handle → close
// src/index.ts (simplified)
function getServer() {
const server = createMCPServer();
registerCreateUserTool(server);
registerFetchUserTool(server);
registerAllUsersResource(server);
registerAllTodoResources(server);
registerSingleTodoResource(server);
registerFetchPrompt(server);
return server;
}
app.all('/mcp', async (req, res) => {
const server = getServer();
const transport = new StreamableHTTPServerTransport();
await server.connect(transport);
await transport.handleRequest(req, res, req.body ?? {});
res.on('close', () => {
server.close();
transport.close();
});
});
---
Server Factory (src/server.ts)
The server is created per request to support stateless HTTP:
import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
export function createMCPServer() {
return new McpServer(
{ name: 'emi_mcp_server', version: '1.0.0' },
{
capabilities: {
tools: {},
prompts: {},
resources: {},
tasks: {}
}
}
);
}
---
Registration Pattern
Tools, resources, and prompts use registration functions that accept a server instance. This allows a new server to be created per request and configured before use.
Example: fetch-users tool
import type { McpServer } from '@modelcontextprotocol/sdk/server/mcp.js';
export function registerFetchUserTool(server: McpServer) {
server.registerTool(
'fetch-users',
{ title: '...', description: '...', inputSchema: fetchUserSchema },
async (userSearch) => ({ content: [{ type: 'text', text: JSON.stringify(foundUsers) }] })
);
}
---
Resources
Static Resources
| Resource | URI | Description | |----------|-----|-------------| | users | users://all | All users from users.json | | todos | todos://all | All todos from dummyjson.com API |
Resource Templates
| Resource | URI Template | Description | |----------|--------------|-------------| | single-todo | todos://{id}/single | Fetch a single todo by ID |
Resource templates appear in the Templates section of the MCP Inspector. To read a single todo, request e.g. todos://5/single.
Return format: { contents: [{ uri: string, text: string }] }
---
Prompts
Prompts are reusable templates for AI interactions. In Cursor, type / in the chat to see available prompts.
| Prompt | Args | Description | |--------|------|-------------| | fetch-todo-item | id (number) | Generates a prompt to fetch a todo by ID |
Example: /fetch-todo-item with id: 1 → "go and get a todo item based on 1"
---
Adding the Server to Cursor
Option A: Local (stdio via mcp-remote)
If running the HTTP server locally, use mcp-remote to proxy:
{
"mcpServers": {
"tc_mcp_iii": {
"command": "npx",
"args": ["-y", "mcp-remote", "http://localhost:3000/mcp"],
"cwd": "C:\\code\\MCP\\tc_mcp_III"
}
}
}
Option B: Direct URL (if Cursor supports it)
{
"mcpServers": {
"tc_mcp_iii": {
"url": "http://localhost:3000/mcp"
}
}
}
Option C: Cloud deployment
For a server deployed on Cloud Run or similar:
{
"mcpServers": {
"tc_mcp_iii": {
"command": "npx",
"args": ["-y", "mcp-remote", "https://YOUR-SERVICE.run.app/mcp"]
}
}
}
---
Testing with MCP Inspector
Connect via URL (Streamable HTTP)
- Terminal 1 – Start the server:
npm run dev
- Terminal 2 – Launch Inspector and connect to URL:
npx @modelcontextprotocol/inspector --connect http://localhost:3000/mcp
- In the Inspector UI, select streamable-http as the transport and enter
http://localhost:3000/mcpif prompted.
Connect via stdio (legacy)
The npm run inspect script spawns the server as a child process. For Streamable HTTP testing, use the two-terminal approach above.
---
Available Tools
| Tool | Description | Required params | |------|-------------|-----------------| | create-user | Create a new user | name, email, phone (address optional) | | fetch-users | Search users | name, email, phone |
Available Resources
| Resource | URI | Description | |----------|-----|-------------| | users | users://all | All users from users.json | | todos | todos://all | All todos from dummyjson.com | | single-todo | todos://{id}/single | Single todo by ID (template) |
Available Prompts
| Prompt | Args | Description | |--------|------|-------------| | fetch-todo-item | id (number) | Generate a prompt to fetch a todo by ID |
---
Cloud Deployment (GCP Cloud Run)
The server is ready for cloud deployment:
- Build & deploy:
gcloud run deploy tc-mcp-server --source .
- Environment: Set
PORT(Cloud Run uses 8080 by default).
- Client config: Point Cursor or Inspector to
https://YOUR-SERVICE.run.app/mcp.
- Auth: Use
gcloud run services proxyfor local clients, or OIDC/IAM for production.
See Host MCP servers on Cloud Run for details.
---
Troubleshooting
| Issue | Solution | |-------|----------| | Tools not showing | Ensure all registerXxx(server) are called in getServer() | | "Already connected to a transport" | Use per-request server pattern: create server in handler, call server.close() on response close | | Inspector URL not connecting | Start server with npm run dev first, then --connect http://localhost:3000/mcp | | Prompts not in Cursor | Type / in chat; ensure server is configured and connected | | Single-todo not in Resources list | It's a template—check the Templates section, or read todos://1/single directly | | Transport type error | Use transport as Transport with exactOptionalPropertyTypes |
---






