Server data from the Official MCP Registry
AI image generation and editing with Google Gemini. Structured JSON editing.
AI image generation and editing with Google Gemini. Structured JSON editing.
Valid MCP server (2 strong, 2 medium validity signals). No known CVEs in dependencies. Package registry verified. Imported from the Official MCP Registry.
12 files analyzed · 1 issue found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
This plugin requests these system permissions. Most are normal for its category.
Set these up before or after installing:
Environment variable: GEMINI_API_KEY
Add this to your MCP configuration file:
{
"mcpServers": {
"io-github-udhaykumarbala-gemini-image-studio": {
"env": {
"GEMINI_API_KEY": "your-gemini-api-key-here"
},
"args": [
"-y",
"gemini-image-studio-mcp"
],
"command": "npx"
}
}
}From the project's GitHub README.
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, style_modifiers, and meta sections — each field precisely describing the image's visual components.
edit_imageEdit an image using JSON changes or natural language.
| Parameter | Type | Required | Description |
|---|---|---|---|
image_path | string | Yes | Path to the image |
edit_type | "json" | "natural_language" | Yes | Edit mode |
changes | object | For JSON edits | Dot-notation paths to change |
instruction | string | For NL edits | Natural language instruction |
blueprint | object | No | Blueprint (auto-loaded from cache if omitted) |
model | "flash" | "pro" | No | Model (default: "flash") |
output_name | string | No | Custom filename |
JSON edit example — change hair color and add sunglasses:
{
"image_path": "/output/portrait.png",
"edit_type": "json",
"changes": {
"subject[0].hair.color": "platinum_blonde",
"subject[0].accessories": [
{ "item": "sunglasses", "material": "metal", "color": "#C0C0C0" }
]
}
}
Natural language edit example:
{
"image_path": "/output/portrait.png",
"edit_type": "natural_language",
"instruction": "Change the background to a tropical beach at sunset. Keep the person exactly the same."
}
get_presetsList available asset presets with dimensions, tips, and conventions.
| Parameter | Type | Required | Description |
|---|---|---|---|
category | "ad" | "web" | "social" | "all" | No | Filter (default: "all") |
list_generatedBrowse previously generated images.
| Parameter | Type | Required | Description |
|---|---|---|---|
filter | string | No | Search by filename |
limit | number | No | Max results (default: 20) |
include_blueprints | boolean | No | Include cached blueprints |
The key differentiator — precise, field-level image editing:
Step 1: Generate
generate_image(prompt: "Professional headshot, navy blazer", preset: "linkedin_post")
→ /output/headshot.png
Step 2: Decompose
decompose_image(image_path: "/output/headshot.png")
→ JSON blueprint with every visual component mapped
Step 3: Edit (precise)
edit_image(
image_path: "/output/headshot.png",
edit_type: "json",
changes: {
"subject[0].clothing[0].color": "#8B0000",
"scene.lighting.type": "studio_softbox"
}
)
→ /output/headshot-edit-1.png (blazer changed to dark red, lighting adjusted)
Step 4: Edit (creative)
edit_image(
image_path: "/output/headshot-edit-1.png",
edit_type: "natural_language",
instruction: "Add warm bokeh to the background"
)
→ /output/headshot-edit-1-edit-1.png
subject[0].hair.color → Hair color
subject[0].hair.style → Hair style
subject[0].clothing[0].color → First clothing item color
subject[0].accessories → Add/change accessories
scene.lighting.type → Lighting type
scene.location → Location/background
text_rendering.text_content → Text in image
technical.lens → Camera lens
composition.framing → Shot framing
style_modifiers.aesthetic → Aesthetic style
| Preset | Category | Aspect Ratio | Dimensions | Best For |
|---|---|---|---|---|
facebook_ad | Ad | 1:1 | 1080x1080 | Facebook/Instagram feed ads |
instagram_story_ad | Ad | 9:16 | 1080x1920 | Instagram/Facebook story ads |
google_display_banner | Ad | 16:9 | 1200x628 | Google Display Network |
hero_image | Web | 21:9 | 2560x1080 | Above-the-fold hero sections |
og_image | Web | 16:9 | 1200x630 | Social share / link previews |
product_card | Web | 4:5 | 800x1000 | E-commerce product grids |
email_header | Web | 3:1 | 600x200 | Email marketing headers |
linkedin_post | Social | 1:1 | 1080x1080 | LinkedIn feed posts |
twitter_post | Social | 16:9 | 1200x675 | Twitter/X posts |
youtube_thumbnail | Social | 16:9 | 1280x720 | YouTube thumbnails |
| Variable | Required | Default | Description |
|---|---|---|---|
GEMINI_API_KEY | Yes | — | Google AI Studio API key |
OUTPUT_DIR | No | ./output | Where generated images are saved |
claude mcp add gemini-image-studio-mcp -e GEMINI_API_KEY=your-key -- gemini-image-studio-mcp
Add to .cursor/mcp.json:
{
"mcpServers": {
"gemini-image-studio-mcp": {
"command": "npx",
"args": ["-y", "gemini-image-studio-mcp"],
"env": {
"GEMINI_API_KEY": "your-key-here"
}
}
}
}
GEMINI_API_KEY=your-key npx gemini-image-studio-mcp
The server communicates over stdio using the Model Context Protocol.
This server also exposes:
nano_banana_expert — invoke this to give Claude full knowledge of the JSON schema, editing best practices, and asset creation guidelinesnanobanana://schema/prompt — the raw JSON schema with all enum values for programmatic access| Model | ID | Best For |
|---|---|---|
| Flash (default) | gemini-3.1-flash-image-preview | Fast generation, high volume, cost-effective |
| Pro | gemini-3-pro-image-preview | Best quality, complex scenes, professional assets |
Contributions welcome! Please:
git checkout -b feature/my-feature)npm test)Be the first to review this server!
by Modelcontextprotocol · AI & ML
Dynamic and reflective problem-solving through structured thought sequences
by Toleno · Developer Tools
Toleno Network MCP Server — Manage your Toleno mining account with Claude AI using natural language.
by mcp-marketplace · Developer Tools
Create, build, and publish Python MCP servers to PyPI — conversationally.
by Microsoft · Content & Media
Convert files (PDF, Word, Excel, images, audio) to Markdown for LLM consumption
by mcp-marketplace · Developer Tools
Scaffold, build, and publish TypeScript MCP servers to npm — conversationally
by mcp-marketplace · Finance
Free stock data and market news for any MCP-compatible AI assistant.