PhotoShoot AI Design
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@PhotoShoot AI DesignGenerate a product photo of a red mug on marble"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
PhotoShoot AI Design
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
Related MCP server: jgkme/kilo-image-gen-mcp
Features
AI Provider Integration
Seamlessly switch between multiple AI providers:
Provider | Models | Best For | Pricing |
700+ models including FLUX, Stable Diffusion, Kling, Veo, Sora | Product photography, video content | Competitive rates | |
Google Gemini's native image generation | Fashion, OOTD, lifestyle | ~$0.02/image | |
DALL-E 3, GPT-4 | Professional portraits, creative concepts | Standard OpenAI pricing | |
Stable Diffusion XL | Custom styles, artistic content | $0.004-$0.02/image | |
Proprietary photoshoot models | E-commerce, brand consistency | Platform pricing | |
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 imagesphotoshoot_edit- Edit and enhance existing imagesphotoshoot_template- Get available templates and stylesphotoshoot_batch- Process multiple images in batchphotoshoot_variations- Generate image variationsphotoshoot_upscale- Upscale images to higher resolution
Skills System
Modular, reusable skills for common design workflows:
Skill | Description | Use Cases |
Professional product photo generation | E-commerce, product listings, catalogs | |
Fashion and lifestyle content creation | Instagram, TikTok, Pinterest fashion | |
AI-powered photo editing and retouching | Post-processing, optimization | |
Brand-consistent visual generation | Campaigns, marketing materials | |
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:startSee 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-designOpenLLM 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=mediumAgent 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 fileAPI 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.aiProvider 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 devPerformance
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.
Links
PhotoShoot App - Main platform
WaveSpeed AI - WaveSpeed documentation
Nano Banana - Google Gemini docs
MCP Specification - Protocol details
Claude Code - Claude Code IDE
Pi Agent - Pi Agent platform
OpenLLM - OpenLLM ecosystem
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
This server cannot be installed
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Related MCP Connectors
MCP server for NanoBanana AI image generation and editing
MCP server for Qwen Image 3 AI image generation
MCP server for Flux AI image generation
MCP server for Wan AI video generation
Related MCP Servers
- AlicenseNot gradedqualityCmaintenanceAI-powered image generation MCP server with 16 specialized tools for generating, editing, analyzing, and processing images using Google's Nano Banana 2 model. Supports custom API endpoints and integrates with AI coding assistants via natural language.641MIT
- AlicenseNot gradedqualityBmaintenanceMCP server for generating, editing, and processing images via multiple providers including Kilo, OpenRouter, OpenAI, and Gemini, with local tools for background removal, resizing, and cropping.182MIT
- AlicenseNot gradedqualityDmaintenanceAn MCP server that provides image generation using Google's Nano Banana Gemini models, with additional tools for background removal, upscaling, and format conversion via deterministic post-processing.1MIT
- AlicenseAqualityAmaintenanceMCP server for AI-powered image generation using Google Gemini Nano Banana models. Enables text-to-image generation, image editing, multi-image combination, and favicon generation directly from your AI coding assistant.239MIT