name: anth-hello-world description: 'Create a minimal working Anthropic Claude Messages API example.

Use when starting a new Claude integration, testing your setup,

or learning basic Messages API patterns for text, vision, and streaming.

Trigger with phrases like "anthropic hello world", "claude api example",

"anthropic quick start", "simple claude code", "first messages api call".

' allowed-tools: Read, Write, Edit version: 1.0.0 license: MIT author: Jeremy Longshore jeremy@intentsolutions.io tags:

• saas
• ai
• anthropic compatibility: Designed for Claude Code

Anthropic Hello World

Overview

Three minimal examples covering the Claude Messages API core surfaces: basic text completion, vision (image analysis), and streaming responses.

Prerequisites

• Completed anth-install-auth setup
• Valid ANTHROPIC_API_KEY in environment
• Python 3.8+ with anthropic package or Node.js 18+ with @anthropic-ai/sdk

Instructions

Example 1: Basic Text Message (Python)

import anthropic

client = anthropic.Anthropic()

message = client.messages.create(
    model="claude-sonnet-4-20250514",
    max_tokens=1024,
    messages=[
        {"role": "user", "content": "Explain quantum computing in 3 sentences."}
    ]
)

# Response structure
print(message.content[0].text)       # The actual text response
print(f"ID: {message.id}")           # msg_01XFDUDYJgAACzvnptvVoYEL
print(f"Model: {message.model}")     # claude-sonnet-4-20250514
print(f"Stop: {message.stop_reason}")# end_turn
print(f"Usage: {message.usage.input_tokens}in / {message.usage.output_tokens}out")

Example 2: Vision — Analyze an Image (TypeScript)

import Anthropic from '@anthropic-ai/sdk';
import * as fs from 'fs';

const client = new Anthropic();

// From file (base64)
const imageData = fs.readFileSync('chart.png').toString('base64');

const message = await client.messages.create({
  model: 'claude-sonnet-4-20250514',
  max_tokens: 1024,
  messages: [{
    role: 'user',
    content: [
      {
        type: 'image',
        source: {
          type: 'base64',
          media_type: 'image/png',
          data: imageData,
        },
      },
      { type: 'text', text: 'Describe what this chart shows.' },
    ],
  }],
});

console.log(message.content[0].type === 'text' ? message.content[0].text : '');

Example 3: Streaming Response (Python)

import anthropic

client = anthropic.Anthropic()

with client.messages.stream(
    model="claude-sonnet-4-20250514",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Write a haiku about APIs."}]
) as stream:
    for text in stream.text_stream:
        print(text, end="", flush=True)

# Get final message with full metadata
final = stream.get_final_message()
print(f"\nTokens used: {final.usage.input_tokens}+{final.usage.output_tokens}")

Output

• Working code file with Claude client initialization
• Successful API response with text content
• Console output showing model response and usage metadata

Error Handling

Key API Parameters

Resources

• Messages API Reference
• Messages Examples
• Vision Guide

Next Steps

Proceed to anth-local-dev-loop for development workflow setup.