MCP Builder

Decision Tree

What are you building?
    ├─ Tool (action the AI can take) → Define tool with input schema
    ├─ Resource (data the AI can read) → Define resource with URI
    └─ Prompt (reusable template) → Define prompt with arguments

What language?
    ├─ TypeScript → See references/typescript-guide.md
    └─ Python → See references/python-guide.md

Quick Start (TypeScript)

npx @anthropic-ai/create-mcp-server my-server
cd my-server && npm install

import { McpServer } from '@anthropic-ai/mcp-server';

const server = new McpServer({ name: 'my-server', version: '1.0.0' });

server.tool('greet', { name: { type: 'string' } }, async ({ name }) => {
  return { content: [{ type: 'text', text: `Hello, ${name}!` }] };
});

server.run();

Quick Start (Python)

pip install mcp

from mcp.server import Server

server = Server("my-server")

@server.tool("greet")
async def greet(name: str) -> str:
    return f"Hello, {name}!"

server.run()

Configuration

Register in

.claude/mcp.json

:

{
  "mcpServers": {
    "my-server": {
      "command": "node",
      "args": ["path/to/my-server/dist/index.js"]
    }
  }
}

Best Practices

• Return structured data (JSON) not just text
• Include error handling with meaningful messages
• Add input validation on all tool parameters
• Keep tools focused (one action per tool)
• Use descriptive names and descriptions (shown to the AI)

For detailed guides see:

• TypeScript MCP guide
• Python MCP guide