mcp-builder

โดย mcp-use

สร้างเซิร์ฟเวอร์ MCP ที่พร้อมใช้งานจริงด้วยเฟรมเวิร์ก mcp-use และการลงทะเบียนวิดเจ็ตอัตโนมัติ เริ่มต้นด้วย npx create-mcp-use-app และเลือกจากสามเทมเพลต: starter (ฟีเจอร์ครบ), mcp-apps (ปรับให้เหมาะกับ ChatGPT), หรือ blank (ขั้นต่ำ) กำหนดเครื่องมือ ทรัพยากร และพร้อมต์โดยใช้สคีมา Zod พร้อมการตรวจสอบอัตโนมัติและคำอธิบายพารามิเตอร์ที่ชัดเจน ลงทะเบียนวิดเจ็ต React จากโฟลเดอร์ resources/ โดยอัตโนมัติเป็นเครื่องมือและทรัพยากร MCP พร้อมรองรับโปรโตคอลคู่สำหรับ MCP Apps และ...

npx skills add https://github.com/mcp-use/skills --skill mcp-builder

ดาวน์โหลด ZIP GitHub

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:

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

# 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:

Server scans resources/ folder at startup
Finds .tsx files or widget.tsx in folders
Extracts widgetMetadata from each component
Registers as MCP Tool (e.g., weather-display)
Registers as MCP Resource (e.g., ui://widget/weather-display.html)
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:

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:

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:

// 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:

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):

yarn dev

Production mode:

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:

mcp-use start --port 3000 --tunnel

Option 2 - Separate tunnel:

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):

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

# Deploy
yarn deploy

If authentication error:

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:

// 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() {
  const { props, isPending } = useWidget<z.infer<typeof propSchema>>();
  
  // Always handle loading state
  if (isPending) return <div>Loading...</div>;
  
  return (
    <McpUseProvider autoSize>
      <div>
        <h2>{props.city}</h2>
        <p>{props.temperature}°C</p>
      </div>
    </McpUseProvider>
  );
}

Widget automatically becomes available as:

MCP Tool: weather-display
MCP Resource: ui://widget/weather-display.html

Content Security Policy (CSP)

Control what external resources widgets can access:

export const widgetMetadata: WidgetMetadata = {
  description: "Weather widget",
  props: z.object({ city: z.string() }),
  metadata: {
    csp: {
      // APIs to call
      connectDomains: ["https://api.weather.com"],
      // Static assets to load
      resourceDomains: ["https://cdn.weather.com"],
      // Iframes to embed
      frameDomains: ["https://embed.weather.com"],
      // Script directives
      scriptDirectives: ["'unsafe-inline'"],
    },
  },
};

Alternatively, set at server level:

server.uiResource({
  type: "mcpApps",
  name: "my-widget",
  htmlTemplate: `...`,
  metadata: {
    csp: {
      connectDomains: ["https://api.example.com"],
      resourceDomains: ["https://cdn.example.com"],
    },
  },
});

Dual-Protocol Widget Support

mcp-use supports the MCP Apps standard (SEP-1865) with automatic dual-protocol support:

import { MCPServer } from 'mcp-use/server';

const server = new MCPServer({
  name: 'my-server',
  version: '1.0.0',
  baseUrl: process.env.MCP_URL || 'http://localhost:3000', // Required for widgets
});

// Register a dual-protocol widget
server.uiResource({
  type: "mcpApps", // Works with BOTH MCP Apps clients AND ChatGPT
  name: "weather-display",
  htmlTemplate: `<!DOCTYPE html>...`,
  metadata: {
    csp: { connectDomains: ["https://api.weather.com"] },
    prefersBorder: true,
    autoResize: true,
  },
});

What happens automatically:

MCP Apps clients (Claude, Goose) receive: text/html;profile=mcp-app with _meta.ui.*
ChatGPT receives: text/html+skybridge with _meta.openai/*
Same widget code works everywhere!

Custom OpenAI Metadata

Need ChatGPT-specific features? Combine both metadata fields:

server.uiResource({
  type: "mcpApps",
  name: "my-widget",
  htmlTemplate: `...`,
  // Unified metadata (dual-protocol)
  metadata: {
    csp: { connectDomains: ["https://api.example.com"] },
    prefersBorder: true,
  },
  // ChatGPT-specific overrides
  appsSdkMetadata: {
    "openai/widgetDescription": "ChatGPT-specific description",
    "openai/customFeature": "some-value", // Any custom OpenAI metadata
  },
});

Project Structure

my-mcp-server/
├── resources/           # React widgets (apps-sdk)
│   └── widget.tsx
├── public/             # Static assets
├── index.ts            # Server entry point
├── package.json
├── tsconfig.json
└── README.md

Common Patterns

Tool with dual-protocol widget:

import { MCPServer, widget, text } from 'mcp-use/server';
import { z } from 'zod';

const server = new MCPServer({
  name: 'my-server',
  version: '1.0.0',
  baseUrl: process.env.MCP_URL || 'http://localhost:3000',
});

server.tool(
  {
    name: "show-data",
    description: "Display data with visualization",
    schema: z.object({
      query: z.string()
    }),
    widget: {
      name: "data-display", // Must exist in resources/
      invoking: "Loading...",
      invoked: "Data loaded"
    }
  },
  async ({ query }) => {
    const data = await fetchData(query);
    return widget({
      props: { data },
      output: text(`Found ${data.length} results`)
    });
  }
);

Resource template (parameterized):

server.resourceTemplate(
  {
    uriTemplate: "user://{userId}/profile",
    name: "User Profile",
    description: "Get user by ID",
    mimeType: "application/json"
  },
  async ({ userId }) => {
    const user = await fetchUser(userId);
    return object(user);
  }
);

Error handling:

server.tool(
  {
    name: "divide",
    schema: z.object({
      a: z.number(),
      b: z.number()
    })
  },
  async ({ a, b }) => {
    if (b === 0) {
      return text("Error: Cannot divide by zero");
    }
    return text(`Result: ${a / b}`);
  }
);