hyc-image-mcp Tutorial: Image Understanding & OCR with MCP + NexaAPI (Python Guide 2026)

#machinelearning #ai #python #tutorial

hyc-image-mcp just dropped as a brand-new MCP server for image understanding and OCR. Let's supercharge it with NexaAPI's multimodal AI at just $0.003/image.

What Is hyc-image-mcp?

hyc-image-mcp is a fresh MCP (Model Context Protocol) server that adds image understanding and OCR to AI assistants like Claude and GPT. It follows the Model Context Protocol standard for seamless LLM integration.

Why Add NexaAPI?

hyc-image-mcp reads images. NexaAPI generates them — plus TTS, video, and more. Together they form a complete multimodal pipeline.

NexaAPI highlights:

50+ models (Flux Pro, GPT Image, Veo 3, Whisper, TTS)
$0.003/image — 5x cheaper than alternatives
Free tier: 100 images at rapidapi.com/user/nexaquency

Python Tutorial

# pip install nexaapi requests
from nexaapi import NexaAPI
import requests, base64

client = NexaAPI(api_key='YOUR_RAPIDAPI_KEY')

def analyze_image_with_mcp(image_path: str) -> dict:
    """Call hyc-image-mcp for OCR + understanding"""
    with open(image_path, 'rb') as f:
        image_data = base64.b64encode(f.read()).decode()

    response = requests.post(
        'http://localhost:3000/analyze',
        json={'image': image_data, 'tasks': ['ocr', 'description']}
    )
    return response.json()

def generate_enhanced_image(description: str) -> str:
    """Generate enhanced image — only $0.003!"""
    result = client.image.generate(
        model='flux-schnell',
        prompt=f'{description}, high quality, detailed',
        width=1024, height=1024
    )
    return result.image_url

def generate_audio_description(text: str) -> str:
    """Convert OCR text to audio"""
    result = client.audio.tts(
        text=text,
        voice='en-US-female',
        model='tts-multilingual'
    )
    return result.audio_url

# Full pipeline
analysis = analyze_image_with_mcp('document.png')
enhanced = generate_enhanced_image(analysis['description'])
audio = generate_audio_description(analysis['ocr_text'])

print(f"✅ Enhanced image: {enhanced}")
print(f"🔊 Audio: {audio}")
print(f"💰 Cost: $0.003")

JavaScript Tutorial

// npm install nexaapi axios
import NexaAPI from 'nexaapi';
import axios from 'axios';
import fs from 'fs';

const client = new NexaAPI({ apiKey: 'YOUR_RAPIDAPI_KEY' });

async function analyzeWithHycMcp(imagePath) {
  const imageData = fs.readFileSync(imagePath).toString('base64');
  const { data } = await axios.post('http://localhost:3000/analyze', {
    image: imageData,
    tasks: ['ocr', 'description']
  });
  return data;
}

async function fullPipeline(imagePath) {
  // Step 1: OCR + understanding via hyc-image-mcp
  const analysis = await analyzeWithHycMcp(imagePath);

  // Step 2: Generate enhanced image via NexaAPI ($0.003)
  const enhanced = await client.image.generate({
    model: 'flux-schnell',
    prompt: `${analysis.description}, ultra detailed`,
    width: 1024, height: 1024
  });

  // Step 3: TTS for accessibility
  const tts = await client.audio.tts({
    text: `Image contains: ${analysis.description}`,
    voice: 'en-US-neural'
  });

  return {
    ocrText: analysis.ocr_text,
    enhancedImage: enhanced.imageUrl,  // $0.003
    audioDescription: tts.audioUrl
  };
}

const result = await fullPipeline('invoice.png');
console.log('Enhanced:', result.enhancedImage);