nano-banana-mcp

nano-banana-mcp

MCP server for generating and editing images using Google Gemini API. Supports text-to-image generation, image editing, and image description.

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README

nano-banana-mcp

npm

Nano Banana MCP server for generating and editing images with Google Gemini. No Gemini CLI required -- just an API key.

Quick Start

  1. Get a Gemini API key from Google AI Studio

  2. Add to your Claude Code settings (~/.claude/settings.json) or Claude Desktop config:

{
  "mcpServers": {
    "nano-banana": {
      "command": "npx",
      "args": ["-y", "@daniel.barta/nano-banana-mcp"],
      "env": {
        "GEMINI_API_KEY": "your-api-key"
      }
    }
  }
}
  1. Restart Claude and ask it to generate an image.

Configuration

Environment Variable Required Default Description
GEMINI_API_KEY Yes -- Your Google AI API key
GEMINI_MODEL No gemini-3.1-flash-image-preview Gemini model for image generation/editing
GEMINI_DESCRIBE_MODEL No gemini-2.5-flash Gemini model for image description (text-only output)
GEMINI_BASE_URL No -- Custom base URL for Gemini API (proxy support)
OUTPUT_DIR No ~/nano-banana-output Directory for saved images

Supported Models

Model Notes
gemini-3.1-flash-image-preview Default. Latest, fastest
gemini-3-pro-image-preview Higher quality, slower
gemini-2.5-flash-image Fast, cost-effective

Tools

generate_image

Generate an image from a text prompt. Supports batch generation (up to 4 images). Response contains a thumbnail preview; full-res image is saved to disk.

Parameter Type Required Description
prompt string Yes Text description of the image
aspectRatio string No Aspect ratio (1:1, 1:4, 1:8, 2:3, 3:2, 3:4, 4:1, 4:3, 4:5, 5:4, 8:1, 9:16, 16:9, 21:9)
size string No Image size (512px, 1K, 2K, 4K)
n number No Number of images to generate (1-4, default 1)
negativePrompt string No Things to exclude from the generated image
systemInstruction string No System instruction to guide the model

edit_image

Edit an existing image based on a text instruction. Supports multi-image input (up to 10 images total). Response contains a thumbnail preview; full-res image is saved to disk.

Parameter Type Required Description
prompt string Yes What to change
filePath string Yes Path to the source image
additionalFilePaths string[] No Additional image paths (up to 9) for multi-image editing
aspectRatio string No Aspect ratio (1:1, 1:4, 1:8, 2:3, 3:2, 3:4, 4:1, 4:3, 4:5, 5:4, 8:1, 9:16, 16:9, 21:9)
size string No Image size (512px, 1K, 2K, 4K)
negativePrompt string No Things to exclude from the edited image
systemInstruction string No System instruction to guide the model

describe_image

Get a text description of an image.

Parameter Type Required Description
filePath string Yes Path to the image
question string No Specific question about the image
systemInstruction string No System instruction to guide the model

Supported Input Formats

For edit_image and describe_image, the following image formats are supported:

JPEG, PNG, WebP, GIF, BMP, TIFF, SVG, HEIC/HEIF

File Path Resolution

When you provide a file path for editing or describing, the server searches for the file in this order:

  1. Absolute path as given
  2. Relative to the current working directory
  3. Relative to the output directory
  4. Basename only in the output directory

Thumbnails

To avoid hitting Claude Code's session file size limits, MCP responses contain thumbnail previews (max 512px, JPEG quality 80, ~20-50KB) instead of full-resolution images. Full-res images are always saved to disk at the path shown in the response metadata.

The first content block in generate/edit responses is a JSON metadata object:

{
  "model": "gemini-3.1-flash-image-preview",
  "count": 1,
  "images": [
    { "filePath": "/Users/you/nano-banana-output/a-cat-1234567890.png", "mimeType": "image/png" }
  ]
}

Development

git clone https://github.com/bartadaniel/nano-banana-mcp.git
cd nano-banana-mcp
npm install
npm run build

Use the local build in your config:

{
  "mcpServers": {
    "nano-banana": {
      "command": "node",
      "args": ["path/to/nano-banana-mcp/dist/index.js"],
      "env": {
        "GEMINI_API_KEY": "your-api-key"
      }
    }
  }
}

Testing

npm test

Runs unit tests using Node.js built-in test runner (node:test). Tests cover error classes, all documented Gemini API response codes (BlockedReason, FinishReason), config shapes, image extraction edge cases, file operations, path security, and thumbnail generation.

License

MIT

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