Skip to main content
Glama

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

Related MCP server: jgkme/kilo-image-gen-mcp

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.

Related MCP Connectors

Related MCP Servers