AI image generation and editing with Google Gemini. Structured JSON editing.
Config is the same across clients — only the file and path differ.
{
"mcpServers": {
"gemini-image-studio-mcp": {
"env": {
"GEMINI_API_KEY": "your-key-here"
},
"args": [
"-y",
"gemini-image-studio-mcp"
],
"command": "npx"
}
}
}Are you the author?
Add this badge to your README to show your security score and help users find safe servers.
MCP server for AI image generation and editing with Google Gemini. Create web assets, ad creatives, and brand visuals — with structured JSON editing for precise, repeatable control.
Run this in your terminal to verify the server starts. Then let us know if it worked — your result helps other developers.
npx -y 'gemini-image-studio-mcp' 2>&1 | head -1 && echo "✓ Server started successfully"
After testing, let us know if it worked:
Five weighted categories — click any category to see the underlying evidence.
No known CVEs.
Checked gemini-image-studio-mcp against OSV.dev.
Click any tool to inspect its schema.
Be the first to review
Have you used this server?
Share your experience — it helps other developers decide.
Sign in to write a review.
Others in ai-ml / design
Persistent memory using a knowledge graph
Dynamic problem-solving through sequential thought chains
MCP server for accessing Figma plugin console logs and screenshots via Cloudflare Workers or local mode
Workspace template + MCP server for Claude Code, Codex CLI, Cursor & Windsurf. Multi-agent knowledge engine (ag-refresh / ag-ask) that turns any codebase into a queryable AI assistant.
MCP Security Weekly
Get CVE alerts and security updates for Gemini Image Studio MCP Server and similar servers.
Start a conversation
Ask a question, share a tip, or report an issue.
Sign in to join the discussion.
MCP server for AI image generation and editing with Google Gemini. Create web assets, ad creatives, and brand visuals — with structured JSON editing for precise, repeatable control.
Most Gemini image MCP servers are basic text-to-image wrappers. This one adds a structured editing pipeline:
subject[0].hair.color: "platinum_blonde" — and regeneratingThis means precise, isolated changes without affecting the rest of the image. Change a hair color without touching the background. Swap clothing without altering the pose. All through dot-notation JSON paths.
Get one free at Google AI Studio.
npm install -g gemini-image-studio-mcp
claude mcp add gemini-image-studio-mcp -e GEMINI_API_KEY=your-key-here -- gemini-image-studio-mcp
Or add to your project's .claude/mcp.json:
{
"mcpServers": {
"gemini-image-studio-mcp": {
"command": "npx",
"args": ["-y", "gemini-image-studio-mcp"],
"env": {
"GEMINI_API_KEY": "your-key-here"
}
}
}
}
Ask Claude to generate images:
"Create a Facebook ad for a coffee shop with warm lighting"
"Generate a hero image for a tech startup landing page"
"Edit the hero image — change the background to a sunset beach"
generate_imageCreate a new image from text or structured JSON prompts.
| Parameter | Type | Required | Description |
|---|---|---|---|
prompt | string | Yes | Text description or JSON prompt |
prompt_format | "text" | "json" | No | Prompt format (default: "text") |
preset | string | No | Asset preset (e.g., "facebook_ad", "hero_image") |
aspect_ratio | string | No | Override ratio ("1:1", "16:9", "9:16", etc.) |
image_size | "1K" | "2K" | "4K" | No | Resolution (default: "1K") |
model | "flash" | "pro" | No | Gemini model (default: "flash") |
reference_images | string[] | No | Paths to reference images for consistency |
output_name | string | No | Custom filename |
enable_search_grounding | boolean | No | Use Google Search for accuracy |
decompose_imageAnalyze an image into a structured JSON blueprint — the first step of the edit workflow.
| Parameter | Type | Required | Description |
|---|---|---|---|
image_path | string | Yes | Path to the image |
detail_level | "basic" | "detailed" | "exhaustive" | No | Granularity (default: "detailed") |
Returns a full blueprint with subject, scene, technical, composition, text_rendering, `s