imagegen

imagegen

Local-first MCP image generation server supporting OpenAI and Google Gemini models for generating and editing images, with an embedded interactive studio.

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imagegen

Local-first MCP image generation server with multi-model support and an embedded interactive studio.

Generate and edit AI images through OpenAI GPT Image and Google Gemini models via the Model Context Protocol (MCP). Includes a built-in studio UI for visual iteration directly inside the chat surface.

Works with any MCP-compatible client: Claude Desktop, Cursor, Windsurf, AnythingLLM, and other AI platforms.

Features

  • Multi-model support -- OpenAI GPT Image 1.5, GPT Image 1 Mini, Google Gemini 3.1 Flash, Gemini 3 Pro, Gemini 2.5 Flash
  • Image generation -- create images from detailed text prompts with configurable aspect ratios and quality profiles
  • Image editing -- modify existing images with natural language instructions and optional reference images
  • Embedded studio -- interactive MCP App for browsing assets, switching models, adjusting settings, and iterating visually
  • Local asset storage -- all generated and uploaded images are persisted locally with full history
  • Enterprise-ready -- configurable model access, concurrency limits, and provider API key management

Tools

Model-visible

These tools are exposed to the AI model:

Tool Description
imagegen_generate Generate a new image from a detailed text prompt
imagegen_edit Edit an existing image using instructions and optional reference images
imagegen_list_models List enabled image models and their capabilities

App-only

These tools are used internally by the embedded studio UI and are not visible to the AI model:

imagegen_list_assets, imagegen_read_asset_bytes, imagegen_create_upload, imagegen_append_upload_chunk, imagegen_finalize_upload

Quick start

Prerequisites: Node.js >= 24, pnpm

git clone https://github.com/CCimen/imagegen.git
cd imagegen
pnpm install
cp .env.example .env

Set at least one provider API key in .env:

OPENAI_API_KEY=sk-...
# and/or
GOOGLE_API_KEY=AI...

Start the server:

pnpm dev

The Streamable HTTP endpoint is available at:

http://127.0.0.1:3001/mcp

Configuration

Variable Default Description
OPENAI_API_KEY -- OpenAI API key (required for GPT Image models)
GOOGLE_API_KEY -- Google AI API key (required for Gemini Image models)
MCP_IMAGEGEN_DATA_DIR ~/.mcp-imagegen Local directory for generated assets
IMAGEGEN_ENABLED_MODELS gpt-image-1.5,gemini-3.1-flash-image-preview Comma-separated list of enabled model IDs
IMAGEGEN_DEFAULT_MODEL gpt-image-1.5 Model used when none is specified
IMAGEGEN_CONCURRENCY_LIMIT 2 Max concurrent image generation requests
IMAGEGEN_HTTP_HOST 127.0.0.1 Server bind address
IMAGEGEN_HTTP_PORT 3001 Server port

MCP client configuration

Add this to your MCP client configuration (e.g. claude_desktop_config.json):

{
  "mcpServers": {
    "imagegen": {
      "url": "http://127.0.0.1:3001/mcp"
    }
  }
}

Docker: If connecting from inside a container, use http://host.docker.internal:3001/mcp instead of 127.0.0.1.

Supported models

Model Provider Highlights
gpt-image-1.5 OpenAI State-of-the-art image generation and editing
gpt-image-1-mini OpenAI Cost-efficient variant with editing support
gemini-3.1-flash-image-preview Google Fast generation with thinking controls
gemini-3-pro-image-preview Google High-fidelity text rendering
gemini-2.5-flash-image Google Low-latency generation

Models are enabled via IMAGEGEN_ENABLED_MODELS in .env. The server fails fast on startup if no enabled models have valid API keys configured.

Development

pnpm dev          # build studio + start server in watch mode
pnpm test         # run all tests
pnpm test:e2e     # run end-to-end server tests
pnpm build        # production build
pnpm start        # start production server
pnpm check        # type-check all packages

License

AGPL-3.0-only

If you run a modified version of this server for users over a network, you must make the corresponding source available to those users, as required by the AGPL.

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