mcp-nano-banana
Provides AI-powered image generation, editing, and combination using Google Gemini models (Nano Banana Pro, Nano Banana 2, Nano Banana). Supports text-to-image, image editing with reference images, and multi-image composition at various resolutions and aspect ratios.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@mcp-nano-bananacreate a 1024x1024 image of a futuristic robot holding a banana"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
mcp-nano-banana
MCP server for AI-powered image generation using Google Gemini Nano Banana models. Generate, edit, and combine images from text prompts — directly from your AI coding assistant.
Features
Text-to-image generation — Create images from natural language descriptions
Image editing — Upload images and modify them with text instructions
Multi-image combination — Mix up to 14 reference images into one composite
Resolution control — Generate at 512px, 1K, 2K, or 4K resolution
13+ aspect ratios — From square (1:1) to ultra-wide (21:9) and tall (1:8)
Auto-fallback — Pro model falls back to Flash on rate limits (429/403/402)
File output — Save to specific paths or return inline base64
Favicon generation — Generate complete favicon packages with one command
Multi-format output — PNG, JPEG, and WebP support
Related MCP server: Nano-Banana MCP Server
Quick Start
Prerequisites
Get a Gemini API key from Google AI Studio
Enable billing on your Google Cloud project — image generation requires a paid tier (~$0.04-0.05/image for NB2 at standard resolution)
Installation
npm install -g mcp-nano-bananaSet your API key:
export GEMINI_API_KEY=your-api-keyFor MCP Registry publication metadata, the registry name is io.github.codeFi/mcp-nano-banana.
MCP Configuration
Codex
codex mcp add nano-banana --env GEMINI_API_KEY=your-api-key -- npx -y mcp-nano-banana@latestOr add manually to ~/.codex/config.toml:
[mcp_servers.nano-banana]
command = "npx"
args = ["-y", "mcp-nano-banana@latest"]
[mcp_servers.nano-banana.env]
GEMINI_API_KEY = "your-api-key"Qwen Code
Add to ~/.qwen/settings.json:
{
"mcpServers": {
"nano-banana": {
"command": "npx",
"args": ["-y", "mcp-nano-banana@latest"],
"env": {
"GEMINI_API_KEY": "your-api-key"
}
}
}
}Claude Code
claude mcp add nano-banana -e GEMINI_API_KEY=your-api-key -- npx -y mcp-nano-banana@latestOr add manually to ~/.claude/claude_desktop_config.json:
{
"mcpServers": {
"nano-banana": {
"command": "npx",
"args": ["-y", "mcp-nano-banana@latest"],
"env": {
"GEMINI_API_KEY": "your-api-key"
}
}
}
}Other MCP Clients
For CLIs and desktop clients that use the standard mcpServers JSON format, register:
{
"mcpServers": {
"nano-banana": {
"command": "npx",
"args": ["-y", "mcp-nano-banana@latest"],
"env": {
"GEMINI_API_KEY": "your-api-key"
}
}
}
}Local / Development Build
git clone https://github.com/codeFi/mcp-nano-banana.git
cd mcp-nano-banana
npm install
npm run buildThen register with your MCP client:
{
"mcpServers": {
"nano-banana": {
"command": "node",
"args": ["/path/to/mcp-nano-banana/dist/index.js"],
"env": {
"GEMINI_API_KEY": "your-api-key"
}
}
}
}Models
Model | MCP Name | Description | Max Ref Images |
| Nano Banana Pro | High quality, thinking mode, professional assets | 6 object + 5 character |
| Nano Banana 2 | Fast, high-efficiency, 1:4/4:1/1:8/8:1 ratios | 10 object + 4 character |
| Nano Banana | Fastest, optimized for high-volume tasks | - |
The server defaults to Nano Banana Pro for best quality and automatically falls back to Flash on rate limits.
Available Parameters
Resolution
Value | Approx. Pixels | Supported Models |
| ~512px | Nano Banana 2 only |
| ~1024px | All models |
| ~2048px | All models |
| ~4096px | All models |
Default: "1K"
Aspect Ratio
Value | Dimensions at 1K | Common Use Case |
| 1024×1024 | Social posts, icons |
| 1344×768 | Headers, presentations |
| 768×1344 | Stories, mobile |
| 1152×896 | Desktop, photos |
| 896×1152 | Portraits |
| ~896×1344 | Print, magazines |
| ~1344×896 | Photos |
| ~896×1120 | Instagram posts |
| ~1120×896 | Instagram landscape |
| ~2048×878 | Ultra-wide banners |
| ~512×2048 | Nano Banana 2 only — tall strips |
| ~2048×512 | Nano Banana 2 only — wide strips |
| ~512×4096 | Nano Banana 2 only — extra tall |
| ~4096×512 | Nano Banana 2 only — extra wide |
Tools
generate_image
Generate or edit images from text prompts.
Parameter | Type | Required | Default | Description |
| string | ✅ Yes | — | Text description or editing instructions |
| string[] | No | — | Reference image paths on disk (up to 14) |
| string | No |
| Model to use |
| string | No |
| See table above for all options |
| string | No |
|
|
| string | No |
|
|
| string | No | — | Save image to this file path |
Examples
Generate from text:
{
"prompt": "A sunset over mountains with dramatic lighting",
"aspectRatio": "16:9",
"resolution": "2K",
"outputPath": "/Users/currentUser/Desktop/sunset.png"
}Edit an existing image:
{
"prompt": "Change the background to a coffee shop interior",
"imagePaths": ["/Users/currentUser/photo.jpg"],
"outputPath": "/Users/currentUser/edited.png"
}Combine multiple images:
{
"prompt": "Put these glasses on this person's face",
"imagePaths": ["/path/to/face.jpg", "/path/to/glasses.jpg"],
"outputPath": "/path/to/result.png"
}High-res wallpaper:
{
"prompt": "A futuristic cityscape at night with neon lights and rain",
"aspectRatio": "16:9",
"resolution": "4K",
"outputPath": "/path/to/wallpaper.png"
}generate_favicons
Generate a complete favicon package from a prompt or existing image.
Parameter | Type | Required | Default | Description |
| string | No* | — | Icon description (required if |
| string | No* | — | Path to existing master icon image |
| string | No |
| Model for prompt generation |
| string | No | — | Directory for individual favicon files |
| string | No | — | Save ZIP package to this path |
| boolean | No |
| Return ZIP as base64 text |
| string | No |
| Manifest |
| string | No |
| Manifest |
| string | No |
| Manifest theme color |
| string | No |
| Manifest background color |
| boolean | No |
| Include README.md in package |
Example
{
"prompt": "A minimalist banana icon with a soft gradient",
"outputDir": "/path/to/favicon",
"outputPath": "/path/to/favicon.zip",
"appName": "MyBrand",
"shortName": "Brand",
"themeColor": "#1a1a2e",
"backgroundColor": "#ffffff"
}Generated files:
favicon.ico— Multi-size icon (16/32/48px)favicon-16x16.png— Browser tabsfavicon-32x32.png— Higher-res tabsapple-touch-icon.png— iOS home screenandroid-chrome-192x192.png— Androidandroid-chrome-512x512.png— Android HDsite.webmanifest— PWA manifest
HTML snippet (included in response):
<link rel="icon" href="/favicon.ico" sizes="any">
<link rel="apple-touch-icon" sizes="180x180" href="/apple-touch-icon.png">
<link rel="icon" type="image/png" sizes="32x32" href="/favicon-32x32.png">
<link rel="icon" type="image/png" sizes="16x16" href="/favicon-16x16.png">
<link rel="manifest" href="/site.webmanifest">Pricing
Image generation requires a paid Google AI Studio account. Approximate costs:
Model | 1K | 2K | 4K |
Nano Banana 2 | ~$0.04 | ~$0.08 | ~$0.15 |
Nano Banana Pro | ~$0.06 | ~$0.13 | ~$0.24 |
You only pay for what you generate — no monthly minimum.
Supported Image Formats
Input (reference images): png, jpg, jpeg, webp, gif
Output: png, jpeg, webp
Development
# Build TypeScript
npm run build
# Watch mode
npm run dev
# Run tests
npm test
# Run the server directly
node dist/index.jsTroubleshooting
Issue | Solution |
| Export the env var or add it to your MCP config |
| Server auto-falls back to Flash model. Add billing to your account. |
| Enable billing at Google Cloud Console |
| High demand — retry in a moment. Common with 4K requests. |
Image not updating after edit | Make sure you rebuilt the TypeScript ( |
| Use absolute paths. Relative paths may not resolve correctly. |
Architecture
AI Assistant (MCP Client)
│ (MCP Protocol over stdio)
▼
mcp-nano-banana Server
│ (HTTPS POST)
▼
Google Gemini API
│
▼
Generated Image → saved to outputPath (or returned inline base64)License
Author
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Maintenance
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