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ai-image-gen-mcp

Scalable MCP backend optimized for Claude Code and Claude Desktop — secure, low-latency, plug-and-play.

Install / Use

claude mcp add krystian-ai -- npx -y github:krystian-ai/ai-image-gen-mcp

If the server publishes to npm under a different name, use that package instead — check the repo README.

About this skill
🔌

MCP Server

Model Context Protocol server

Quality Score

68/100

Supported Platforms

Claude Code
Claude Desktop
Zed

Our assessment of ai-image-gen-mcp

ai-image-gen-mcp scores 68/100 on our quality scale, 474th of 542 AI & Machine Learning skills we index.

Its MCP Server is 8.8 KB long, well organised into 36 sections with 14 code examples: a thorough specification that gives an agent plenty to work with.

It has 3 GitHub stars, so there is little community track record yet; judge it on its content.

Substance
29/30
Structure
20/20
Description
12/15
Adoption
3/20
Freshness
5/15

Maintenance, license and trust

  • The repository was last updated about 14 months ago. Expect some instructions to reference tool versions or APIs that have since changed.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 80/100, with 2 cautions from licensing, adoption, age or documentation. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

ai-image-gen-mcp compared with similar skills

All 4 of these similar skills score higher than ai-image-gen-mcp; compare them before choosing.

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Frequently asked questions

How do I install ai-image-gen-mcp?
Run claude mcp add krystian-ai -- npx -y github:krystian-ai/ai-image-gen-mcp. The install tabs above show the steps for each supported agent.
Which AI agents does ai-image-gen-mcp work with?
It is written for Claude Code, Claude Desktop and Zed, as a MCP Server file. Other agents that read the same format can often use it too.
Is ai-image-gen-mcp safe to use?
It is MIT-licensed and scores 80/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is ai-image-gen-mcp still maintained?
The repository was last updated about 14 months ago. Expect some instructions to reference tool versions or APIs that have since changed.

AI Image‑Gen MCP Server

Version 0.1.0 – MVP public release
Conforms to the Model Context Protocol spec (2025‑06‑18).

<p align="center"> <img src="assets/logo.png" alt="AI Image Generation MCP Server Logo (DALL-E 3)" width="400"> <img src="assets/logo-gpt.png" alt="AI Image Generation MCP Server Logo (GPT-Image-1)" width="400"> </p>

Python 3.11+ License: MIT Code style: black MCP


What's this?

A production‑ready MCP server that transforms state‑of‑the‑art image generators into plug‑and‑play tools for any MCP‑aware client. Currently shipping with DALL·E 3, DALL·E 2, and experimental GPT‑Image‑1 – all accessible through a unified interface.

Why MCP?

MCP is the USB‑C of AI context: one protocol, endless integrations. Ship one server, hook it into Claude Desktop, Claude Code, VS Code, or your own chatbot – the host handles UI, auth, and conversation flow.

Quick examples

| You ask | The server delivers | | ------------------------------------------------------------- | ----------------------------------------------------------- | | "Design a cyberpunk logo for my startup" | High‑res PNG via DALL·E 3 with style presets | | "Generate 5 variations of this product shot" | Batch generation via DALL·E 2 (n=5 support) | | "Create concept art for a steampunk airship" | Artistic rendering with metadata and prompt history |

If you can describe it, we can render it. 💫


Core MCP Concepts

This server implements all three MCP primitives:

  1. Toolsgenerate_image with model selection, size, and style options
  2. Resources – Available models and their capabilities exposed as MCP resources
  3. Prompts – Built‑in templates for product_mockup and concept_art workflows

Feature Highlights

  • Multi‑Model SupportDALL·E 3 (default), DALL·E 2, and GPT‑Image‑1 via unified API
  • Smart Storage – Local cache with timestamped filenames and JSON metadata
  • Flexible Sizing – From 256×256 thumbnails to 1792×1024 widescreen masterpieces
  • Style Controlvivid or natural rendering (DALL·E 3)
  • Batch Generation – Create up to 10 variations per prompt (DALL·E 2)
  • Claude Integration – First‑class support for Desktop and Code editions

Architecture

graph TD
    Client["MCP Client (Claude Desktop/Code)"] -- JSON‑RPC 2.0 --> Server["Image‑Gen MCP Server"]
    Server --> Router["Model Router"]
    Router -->|OpenAI API| DALLE3["DALL·E 3"]
    Router -->|OpenAI API| DALLE2["DALL·E 2"]
    Router -->|Responses API| GPT["GPT‑Image‑1"]
    Server --> Storage["Local Storage + Metadata"]
    Storage --> Client

Quickstart

Prerequisites

  • Python 3.11+
  • OpenAI API key
  • Claude Desktop or Claude Code (for MCP integration)

Installation

git clone https://github.com/krystian-ai/ai-image-gen-mcp.git
cd ai-image-gen-mcp
python3.11 -m venv .venv && source .venv/bin/activate
pip install -e ".[image,dev]"

Configuration

cp .env.example .env
# Edit .env and add your OpenAI API key

Key settings:

OPENAI_API_KEY=sk-...
MODEL_DEFAULT=dall-e-3
CACHE_DIR=/tmp/ai-image-gen-cache

Run Standalone

# Via MCP CLI
mcp-imageserve stdio

# Direct execution
python -m ai_image_gen_mcp.server --transport=stdio

Claude Desktop Integration

Add to ~/Library/Application Support/Claude/claude_desktop_config.json:

{
  "mcpServers": {
    "ai-image-gen": {
      "command": "/path/to/ai-image-gen-mcp/.venv/bin/python",
      "args": ["-m", "ai_image_gen_mcp.server", "stdio"],
      "transport": "STDIO",
      "env": {
        "PYTHONPATH": "/path/to/ai-image-gen-mcp/src",
        "OPENAI_API_KEY": "your-api-key-here"
      }
    }
  }
}

Claude Code Integration

Option 1: Project‑specific .mcp.json (Recommended)

Drop this in your project root:

{
  "ai-image-gen": {
    "command": "python",
    "args": ["-m", "ai_image_gen_mcp.server", "stdio"],
    "transport": "STDIO",
    "env": {
      "PYTHONPATH": "src",
      "OPENAI_API_KEY": "your-api-key-here"
    }
  }
}

Claude Code auto‑detects and loads it. ✨

Option 2: Global Config

Add to ~/.config/claude-code/settings.json for system‑wide access.


Model Capabilities

| Model | Sizes | Styles | Batch (n) | Speed | Notes | | ------------- | ---------------------------------------- | -------------- | --------- | ---------- | ------------------------------ | | DALL·E 3 | 1024×1024, 1792×1024, 1024×1792 | vivid, natural | 1 | Fast | Best quality, default model | | DALL·E 2 | 256×256, 512×512, 1024×1024 | N/A | 1-10 | Fast | Good for variations | | GPT‑Image‑1 | Fixed (model‑determined) | N/A | 1 | Slow (20s+) | Experimental, may timeout |


Usage Examples

Basic Generation

Generate a minimalist logo for a productivity app

With Parameters

Create a vivid 1792x1024 banner of a futuristic cityscape using dall-e-3

Batch Creation

Generate 5 variations of a coffee cup product photo using dall-e-2

Interactive HTML Demo

Explore the server's capabilities through our interactive web interface:

cd examples/html
open index.html  # macOS
# or
xdg-open index.html  # Linux
# or just open in your browser

The demo showcases:

  • Live Examples – Generated images with their prompts
  • Model Comparison – See outputs from DALL·E 3, DALL·E 2, and GPT-Image-1
  • Interactive Gallery – Carousel of stunning AI-generated artwork
  • Integration Guide – How to connect with Claude Desktop/Code

Perfect for visualizing what's possible before diving into the API!


Development

Testing

pytest                           # Full suite
pytest --cov=ai_image_gen_mcp   # Coverage report
python test_dalle.py            # Live API test

Code Quality

black src/        # Format
ruff check src/   # Lint
mypy src/         # Type check

Project Structure

ai-image-gen-mcp/
├── src/ai_image_gen_mcp/
│   ├── server.py          # FastMCP server entry
│   ├── models/            # Model implementations
│   └── config.py          # Environment config
├── tests/                 # Comprehensive test suite
├── examples/
│   └── html/              # Interactive web demo
├── assets/                # Logo images
└── .mcp.json             # Claude Code config

Troubleshooting

| Issue | Solution | | ---------------------------- | ----------------------------------------------------------- | | MCP not detected | Ensure .mcp.json exists in project root | | API key errors | Check OPENAI_API_KEY in .env or environment | | Import errors | Verify PYTHONPATH includes src/ directory | | GPT‑Image‑1 timeouts | Known issue – use DALL·E models for reliability | | Claude Desktop issues | Use full paths to venv Python executable |


Roadmap

| Version | Focus | Status | | ------- | ---------------------------------------------- | ------------ | | 0.1 | MVP with 3 models, local storage | ✅ Shipped | | 0.2 | S3/GCS storage, signed URLs | 🚧 Planning | | 0.3 | Stable Diffusion, ComfyUI integration | 📋 Backlog | | 0.4 | Inpainting, upscaling, style transfer | 💭 Ideas |


Contributing

Fork → feature branch → PR. Run pre-commit hooks. Keep the vibe technical but approachable.


License

MIT – see LICENSE.


Links

Related Skills

View on GitHub
GitHub Stars3
CategoryAI
Updated1y ago
Forks2

Languages

Python

Trust signals

80/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

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