PhotoShoot AI Design

License: MIT MCP Claude Code Pi Agent OpenLLM

AI-powered photoshoot design tools with MCP servers, reusable skills, and intelligent agents. Supports WaveSpeed AI, Nano Banana, OpenAI, Stability AI, and PhotoShoot App integration.

Quick Setup → | Documentation → | Examples →

Overview

PhotoShoot AI Design extends the photoshoot.app platform with advanced AI agent capabilities through the Model Context Protocol (MCP). This project provides a unified interface to multiple AI image generation services, enabling seamless photoshoot automation for:

E-commerce - Product photography for Amazon, Shopify, and online stores
Fashion - OOTD (Outfit of the Day) content for social media
Marketing - Campaign visuals and brand content
Portraits - Professional headshots and personal branding

Features

AI Provider Integration

Seamlessly switch between multiple AI providers:

Provider	Models	Best For	Pricing
WaveSpeed AI	700+ models including FLUX, Stable Diffusion, Kling, Veo, Sora	Product photography, video content	Competitive rates
Nano Banana	Google Gemini's native image generation	Fashion, OOTD, lifestyle	~$0.02/image
OpenAI	DALL-E 3, GPT-4	Professional portraits, creative concepts	Standard OpenAI pricing
Stability AI	Stable Diffusion XL	Custom styles, artistic content	$0.004-$0.02/image
PhotoShoot App	Proprietary photoshoot models	E-commerce, brand consistency	Platform pricing
fal.ai	Fast inference	Rapid prototyping, batch processing	Pay-per-use

MCP Tools

Complete set of Model Context Protocol tools:

photoshoot_generate - Generate AI photos from text or reference images
photoshoot_edit - Edit and enhance existing images
photoshoot_template - Get available templates and styles
photoshoot_batch - Process multiple images in batch
photoshoot_variations - Generate image variations
photoshoot_upscale - Upscale images to higher resolution

Skills System

Modular, reusable skills for common design workflows:

Skill	Description	Use Cases
`product-photography`	Professional product photo generation	E-commerce, product listings, catalogs
`ootd-fashion`	Fashion and lifestyle content creation	Instagram, TikTok, Pinterest fashion
`image-enhancement`	AI-powered photo editing and retouching	Post-processing, optimization
`brand-style`	Brand-consistent visual generation	Campaigns, marketing materials
`batch-production`	High-volume batch processing	Catalog production, bulk operations

AI Agents

Autonomous agents for complex workflows:

DesignerAgent

Analyze reference images and extract style parameters
Generate photos based on brand guidelines
Create platform-specific content (Amazon, Instagram, TikTok)
Manage template libraries

OptimizerAgent

Batch image enhancement
Platform optimization (Amazon, Shopify, social media)
Background removal and replacement
Watermarking and formatting

Installation

Quick Start (3 minutes)

# Clone the repository
git clone git@github.com:photoshootapp/photoshoot-ai-design.git
cd photoshoot-ai-design

# Install dependencies
npm install

# Configure API keys
cp .env.example .env
# Edit .env and add your API keys

# Start MCP server
npm run mcp:start

See SETUP.md for detailed setup instructions and API key acquisition.

Claude Code Plugin

# Install from plugin marketplace
claude plugin install photoshoot-ai-design

# Or manually configure in .claude/settings.json
{
  "mcpServers": {
    "photoshoot": {
      "command": "node",
      "args": ["packages/mcp-server/dist/index.js"],
      "cwd": "/path/to/photoshoot-ai-design"
    }
  }
}

Pi Agent Plugin

pi-agent plugin add photoshoot-ai-design

OpenLLM Plugin

import openllm

plugin = openllm.load_plugin("photoshoot-ai-design")
model = openllm.start("vllm/nano-banana", plugins=[plugin])

Usage

MCP Tool Examples

// Generate product photography
await mcpClient.callTool({
  name: "photoshoot_generate",
  arguments: {
    type: "product",
    provider: "wavespeed",
    prompt: "Professional product photo of wireless headphones",
    style: "studio",
    quantity: 4
  }
});

// Generate OOTD fashion content
await mcpClient.callTool({
  name: "photoshoot_generate",
  arguments: {
    type: "ootd",
    provider: "nano-banana",
    prompt: "Streetwear fashion photoshoot, urban setting",
    style: "vibrant",
    quantity: 6
  }
});

// Edit and enhance images
await mcpClient.callTool({
  name: "photoshoot_edit",
  arguments: {
    image: "https://example.com/product.jpg",
    provider: "auto",
    edits: {
      lighting: "studio",
      background: "white",
      retouch: true
    }
  }
});

Skill Examples

# Product photography
/photoshoot-design product --reference="product.jpg" --style=studio --platform=amazon

# OOTD fashion
/photoshoot-design ootd --reference="outfit.jpg" --style=streetwear --location=urban

# Image enhancement
/photoshoot-design enhance --image="photo.jpg" --intensity=medium

Agent Examples

import { DesignerAgent, createPhotoShootClient } from '@photoshoot/agents';

const client = await createPhotoShootClient();
const agent = new DesignerAgent(client, {
  defaultStyle: 'studio',
  defaultQuantity: 4
});

// Generate product photography
await agent.generateProductPhotography({
  productImage: 'shoe.jpg',
  style: 'minimalist',
  platform: 'amazon',
  quantity: 8
});

// Create OOTD content
await agent.createOOTDContent({
  outfitImage: 'outfit.jpg',
  style: 'luxury',
  location: 'rooftop',
  vibe: 'chic'
});

// Optimize for platforms
await agent.optimizeForPlatform({
  images: ['img1.jpg', 'img2.jpg'],
  platform: 'instagram'
});

Architecture

photoshoot-ai-design/
├── packages/
│   ├── mcp-server/          # MCP server with all AI providers
│   │   ├── src/
│   │   │   ├── api/clients/ # Individual API clients
│   │   │   │   ├── wavespeed.ts
│   │   │   │   ├── nanobanana.ts
│   │   │   │   ├── openai.ts
│   │   │   │   ├── stability.ts
│   │   │   │   ├── photoshoot.ts
│   │   │   │   └── fal.ts
│   │   │   ├── config.ts
│   │   │   └── index.ts
│   │   └── .env.example
│   │
│   ├── mcp-client/          # MCP client SDK
│   ├── skills/              # Skill definitions (Markdown)
│   ├── agents/              # AI agent implementations
│   │
│   └── plugins/
│       ├── claude-code/     # Claude Code plugin
│       ├── pi-agent/        # Pi Agent plugin
│       └── openllm/         # OpenLLM plugin
│
├── docs/                    # Documentation
├── examples/                # Usage examples
├── .env.example             # Environment configuration template
├── SETUP.md                 # Quick setup guide
└── README.md                # This file

API Reference

MCP Tools

`photoshoot_generate`

Generate photoshoot images using AI.

{
  type: 'product' | 'ootd' | 'portrait',
  provider?: 'wavespeed' | 'nano-banana' | 'openai' | 'stability' | 'auto',
  prompt: string,
  reference?: string,
  style?: string,
  quantity?: number,
  width?: number,
  height?: number
}

`photoshoot_edit`

Edit and enhance images.

{
  image: string,
  provider?: 'wavespeed' | 'nano-banana' | 'openai' | 'stability' | 'auto',
  prompt?: string,
  edits?: {
    lighting?: string,
    background?: string,
    retouch?: boolean,
    enhance?: boolean
  }
}

`photoshoot_batch`

Batch process multiple images.

{
  images: string[],
  operation: 'enhance' | 'resize' | 'format' | 'watermark' | 'remove-background',
  options?: Record<string, unknown>
}

Configuration

Environment Variables

# WaveSpeed AI (recommended for product photography)
WAVESPEED_API_KEY=your_key_here
WAVESPEED_API_URL=https://api.wavespeed.ai/v1

# Nano Banana (Google Gemini - recommended for fashion)
NANO_BANANA_API_KEY=your_key_here
NANO_BANANA_API_URL=https://generativelanguage.googleapis.com/v1beta

# OpenAI (DALL-E)
OPENAI_API_KEY=your_key_here
OPENAI_API_URL=https://api.openai.com/v1

# Stability AI (Stable Diffusion)
STABILITY_API_KEY=your_key_here
STABILITY_API_URL=https://api.stability.ai/v1

# PhotoShoot App
PHOTOSHOOT_API_KEY=your_key_here
PHOTOSHOOT_API_URL=https://api.photoshoot.app

# fal.ai
FAL_API_KEY=your_key_here
FAL_API_URL=https://fal.ai

Provider Selection

The system automatically selects the best provider based on:

Available API keys - Only configured providers are used
Content type - Different providers excel at different types
User preference - Manual override available

Automatic selection logic:

Product photography → WaveSpeed AI
Fashion/OOTD → Nano Banana
Portraits → OpenAI DALL-E
Custom styles → Stability AI
Fallback → PhotoShoot App (demo mode without API key)

Contributing

We welcome contributions! Please see CONTRIBUTING.md for guidelines.

Areas for Contribution

New AI provider integrations
Additional skill definitions
Agent capability enhancements
Plugin support for other platforms
Documentation and examples

Development

# Install dependencies
npm install

# Build all packages
npm run build

# Run MCP server
npm run mcp:start

# Run tests
npm test

# Development mode with hot reload
npm run dev

Performance

Batch Processing: Process up to 100 images simultaneously
Auto Caching: Reduce redundant API calls with intelligent caching
Concurrent Requests: Configurable concurrent request limits
Timeout Protection: Built-in timeout for all API calls

Roadmap

Video generation support (Kling, Veo, Sora via WaveSpeed)
3D model generation
Advanced editing features (inpainting, outpainting)
Real-time style transfer
Mobile app integration
Cloud storage integration
Team collaboration features

License

MIT License - see LICENSE for details.

Support

GitHub Issues: github.com/photoshootapp/photoshoot-ai-design/issues
Email: support@photoshoot.app
Discord: Coming soon

Acknowledgments

Built with:

Model Context Protocol - Standard for AI tool integration
WaveSpeed AI - Unified AI API platform
Google Gemini - Nano Banana image generation
Claude - Anthropic's AI assistant

Built with ❤️ for the AI photography community

PhotoShoot AI Design

Overview

Features

AI Provider Integration

MCP Tools

Skills System

AI Agents

Installation

Quick Start (3 minutes)

Claude Code Plugin

Pi Agent Plugin

OpenLLM Plugin

Usage

MCP Tool Examples

Skill Examples

Agent Examples

Architecture

API Reference

MCP Tools

photoshoot_generate

photoshoot_edit

photoshoot_batch

Configuration

Environment Variables

Provider Selection

Contributing

Areas for Contribution

Development

Performance

Roadmap

License

Links

Support

Acknowledgments

`photoshoot_generate`

`photoshoot_edit`

`photoshoot_batch`