mcp-builder

What this skill does

# MCP Server Builder

Build production-ready MCP servers with the mcp-use framework. This Skill provides quick-start instructions and best practices for creating MCP servers.

## Quick Start

**Always bootstrap with `npx create-mcp-use-app`:**

```bash
npx create-mcp-use-app my-mcp-server
cd my-mcp-server
```

**Choose template based on needs:**
- `--template starter` - Full-featured with all MCP primitives (tools, resources, prompts) + example widgets
- `--template mcp-apps` - Optimized for ChatGPT widgets with product search example
- `--template blank` - Minimal starting point for custom implementation

```bash
# Example: MCP Apps template
npx create-mcp-use-app my-server --template mcp-apps
cd my-server
yarn install
```

**Template Details:**
- **starter**: Best for learning - includes all MCP features plus widgets
- **mcp-apps**: Best for ChatGPT apps - includes product carousel/accordion example
- **blank**: Best for experts - minimal boilerplate

## MCP Apps Structure

### Automatic Widget Registration

The mcp-apps and starter templates automatically discover and register React widgets from the `resources/` folder:

**Single-file widget pattern:**
```
resources/
└── weather-display.tsx  # Widget name becomes "weather-display"
```

**Folder-based widget pattern:**
```
resources/
└── product-search/      # Widget name becomes "product-search"
    ├── widget.tsx       # Entry point (required name!)
    ├── components/      # Sub-components
    ├── hooks/           # Custom hooks
    ├── types.ts
    └── constants.ts
```

**What happens automatically:**
1. Server scans `resources/` folder at startup
2. Finds `.tsx` files or `widget.tsx` in folders
3. Extracts `widgetMetadata` from each component
4. Registers as MCP Tool (e.g., `weather-display`)
5. Registers as MCP Resource (e.g., `ui://widget/weather-display.html`)
6. Builds widget bundles with Vite

**No manual registration needed!** Just export `widgetMetadata` and a default component.

## Defining Tools

Tools are executable functions that AI models can call:

```typescript
import { MCPServer, text, object } from "mcp-use/server";
import { z } from "zod";

const server = new MCPServer({
  name: "my-server",
  version: "1.0.0",
  description: "My MCP server"
});

// Simple tool
server.tool(
  {
    name: "greet-user",
    description: "Greet a user by name",
    schema: z.object({
      name: z.string().describe("The user's name"),
      formal: z.boolean().optional().describe("Use formal greeting")
    })
  },
  async ({ name, formal }) => {
    const greeting = formal ? `Good day, ${name}` : `Hey ${name}!`;
    return text(greeting);
  }
);
```

**Key points:**
- Use Zod for schema validation
- Add `.describe()` to all parameters
- Return appropriate response types (text, object, widget)

## Defining Resources

Resources expose data that clients can read:

```typescript
import { object, text, markdown } from "mcp-use/server";

// Static resource
server.resource(
  {
    uri: "config://settings",
    name: "Application Settings",
    description: "Current configuration",
    mimeType: "application/json"
  },
  async () => {
    return object({
      theme: "dark",
      version: "1.0.0"
    });
  }
);

// Dynamic resource
server.resource(
  {
    uri: "stats://current",
    name: "Current Stats",
    description: "Real-time statistics",
    mimeType: "application/json"
  },
  async () => {
    const stats = await getStats();
    return object(stats);
  }
);

// Markdown resource
server.resource(
  {
    uri: "docs://guide",
    name: "User Guide",
    description: "Documentation",
    mimeType: "text/markdown"
  },
  async () => {
    return markdown("# Guide\n\nWelcome!");
  }
);
```

**Response helpers available:**
- `text(string)` - Plain text
- `object(data)` - JSON objects
- `markdown(string)` - Markdown content
- `html(string)` - HTML content
- `image(buffer, mimeType)` - Binary images
- `audio(buffer, mimeType)` - Audio files
- `binary(buffer, mimeType)` - Binary data
- `mix(...contents)` - Combine multiple content types

**Advanced response examples:**

```typescript
// Audio response
import { audio } from 'mcp-use/server';

// From base64 data
return audio(base64Data, "audio/wav");

// From file path (async)
return await audio("/path/to/audio.mp3");

// Binary data (PDFs, etc.)
import { binary } from 'mcp-use/server';
return binary(pdfBuffer, "application/pdf");

// Mix multiple content types
import { mix, text, object, resource } from 'mcp-use/server';
return mix(
  text("Analysis complete:"),
  object({ score: 95, status: "pass" }),
  resource("report://analysis-123", text("Full report..."))
);
```

## Defining Prompts

Prompts are reusable templates for AI interactions:

```typescript
server.prompt(
  {
    name: "code-review",
    description: "Generate a code review template",
    schema: z.object({
      language: z.string().describe("Programming language"),
      focusArea: z.string().optional().describe("Specific focus area")
    })
  },
  async ({ language, focusArea }) => {
    const focus = focusArea ? ` with focus on ${focusArea}` : "";
    return {
      messages: [
        {
          role: "user",
          content: {
            type: "text",
            text: `Please review this ${language} code${focus}.`
          }
        }
      ]
    };
  }
);
```

## Testing Locally

**Development mode (hot reload):**
```bash
yarn dev
```

**Production mode:**
```bash
yarn build
yarn start
```

**Inspector UI:**
Access at `http://localhost:3000/inspector` to test tools, view resources, and try prompts.

**Tunneling (test with ChatGPT before deploying):**

Option 1 - Auto-tunnel:
```bash
mcp-use start --port 3000 --tunnel
```

Option 2 - Separate tunnel:
```bash
yarn start  # Terminal 1
npx @mcp-use/tunnel 3000  # Terminal 2
```

You'll get a public URL like `https://happy-cat.local.mcp-use.run/mcp`

**Tunnel details:**
- Expires after 24 hours
- Closes after 1 hour of inactivity
- Rate limit: 10 creations/hour, max 5 active per IP

Learn more: https://mcp-use.com/docs/tunneling

## Deployment

**Deploy to mcp-use Cloud (recommended):**

```bash
# Login first (if not already)
npx mcp-use login

# Deploy
yarn deploy
```

**If authentication error:**
```bash
npx mcp-use login
yarn deploy
```

**After deployment:**
- Public URL provided (e.g., `https://your-server.mcp-use.com/mcp`)
- Auto-scaled and monitored
- HTTPS enabled
- Zero-downtime deployments

## Best Practices

**Tool Design:**
- ✅ One tool = one focused capability
- ✅ Descriptive names and descriptions
- ✅ Use `.describe()` on all Zod fields
- ✅ Handle errors gracefully
- ✅ Return helpful error messages

**Resource Design:**
- ✅ Use clear URI schemes (config://, docs://, stats://)
- ✅ Choose appropriate MIME types
- ✅ Use response helpers for cleaner code
- ✅ Make resources dynamic when needed

**Prompt Design:**
- ✅ Keep prompts reusable
- ✅ Use system messages for context
- ✅ Parameterize with Zod schemas
- ✅ Include clear instructions

**Testing:**
- ✅ Test with Inspector UI first
- ✅ Use tunneling to test with real clients before deploying
- ✅ Verify all tools, resources, and prompts work as expected

**Deployment:**
- ✅ Test locally and with tunneling first
- ✅ Run `npx mcp-use login` if deploy fails
- ✅ Version your server semantically
- ✅ Document breaking changes

## Widget Support

### Automatic Widget Registration

When using the `mcp-apps` or `starter` template, widgets in the `resources/` folder are automatically registered:

```tsx
// resources/weather-display.tsx
import { useWidget, McpUseProvider, type WidgetMetadata } from 'mcp-use/react';
import { z } from 'zod';

const propSchema = z.object({
  city: z.string(),
  temperature: z.number()
});

// Required: Export widget metadata
export const widgetMetadata: WidgetMetadata = {
  description: "Display weather information",
  props: propSchema, // Use 'props', not 'schema'!
};

// Required: Export default component
export default function WeatherDisplay