Imagegen — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited Imagegen (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
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.
Gemini 3.1 Flash, Gemini 3 Pro, Gemini 2.5 Flash
configurable aspect ratios and quality profiles
instructions and optional reference images
models, adjusting settings, and iterating visually
locally with full history
provider API key management
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 |
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
Prerequisites: Node.js >= 24, pnpm
git clone https://github.com/CCimen/imagegen.git
cd imagegen
pnpm install
cp .env.example .envSet at least one provider API key in .env:
OPENAI_API_KEY=sk-...
# and/or
GOOGLE_API_KEY=AI...Start the server:
pnpm devThe Streamable HTTP endpoint is available at:
http://127.0.0.1:3001/mcp| 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 |
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, usehttp://host.docker.internal:3001/mcpinstead of127.0.0.1.
| 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 | Fast generation with thinking controls | |
gemini-3-pro-image-preview | High-fidelity text rendering | |
gemini-2.5-flash-image | 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.
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 packagesIf 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.
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.