About NanoBanana Pro 2
NanoBanana Pro 2 is an MCP server for generating and editing images with Pro and Flash models, defaulting to 4K output. It supports reference images, negative prompts, Google Search grounding, and image metadata tracking.
Key features
- 01Choose Pro or Flash models
- 02Generate images and edit with references
- 03Resolution up to 4K
- 04Negative prompts and batch generation
- 05Google Search grounding
- 06Image statistics and storage maintenance
Use cases
- 01Create detailed images of complex scenes
- 02Generate consistent views from reference images
- 03Iterate quickly on simple image concepts
- 04Review generated image counts and storage
MCP support
The server exposes image generation, reference-file upload, output statistics, and storage-maintenance tools to MCP clients.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMENanoBanana MCP Server
MCP server for AI image generation using NanoBanana Pro 2. Supports Pro (maximum quality) and Flash (fast generation) models with default 4K resolution.
Inspired by the nano-banana naming convention used across the MCP community. This is an independent implementation.
Quick Install
pip install nanobanana-imagen-mcp
# or
uvx nanobanana-imagen-mcp --help
Claude Desktop (claude_desktop_config.json):
{
"mcpServers": {
"nanobanana": {
"command": "uvx",
"args": ["nanobanana-imagen-mcp"],
"env": {
"GEMINI_API_KEY": "your_key_here"
}
}
}
}
| Variable | Description | Default |
|---|---|---|
GEMINI_API_KEY | Gemini API key — required for all generation | -- |
IMAGE_OUTPUT_DIR | Directory where generated images are saved | ~/nanobanana-images |
NANOBANANA_DB_PATH | SQLite database path for image metadata | ~/nanobanana-images/images.db |
What It Does
Generates AI images using NanoBanana Pro 2 models. Supports text-to-image generation, image editing with reference images, file uploads, and server maintenance. Produces high-quality images at up to 4K resolution.
Tools (4)
| Tool | Description |
|---|---|
generate_image | Generate images using NanoBanana Pro 2. Supports model selection (Pro/Flash), aspect ratio, resolution (up to 4K), negative prompts, thinking level, grounding, reference images, and batch generation. |
upload_file | Upload a reference image for use in image editing or conditioning. |
show_output_stats | Display statistics about generated images — count, total size, file details. |
maintenance | Server maintenance and cleanup — clear caches, remove temporary files, optimize storage. |
Models
| Model | Engine | Best For |
|---|---|---|
| Pro | Gemini 3 Pro Image | Maximum quality, complex scenes, photorealism |
| Flash | Gemini 3.1 Flash Image | Fast generation, simple scenes, quick iterations |
Configuration
| Variable | Description | Default |
|---|---|---|
GEMINI_API_KEY | Gemini API key (required) | -- |
IMAGE_OUTPUT_DIR | Output directory for generated images | ~/nanobanana-images |
Storage
Generated image metadata is tracked in a SQLite database.
| Variable | Description | Default |
|---|---|---|
NANOBANANA_DB_PATH | Path to the SQLite metadata database | ~/nanobanana-images/images.db |
Opt out of persistent storage by setting NANOBANANA_DB_PATH=:memory:. This uses an in-memory database that is discarded when the server exits — useful for ephemeral or read-only environments. Trade-off: image history is lost on restart; the show_output_stats tool will show an empty database each session.
The database and output directories are created lazily on first image generation — starting the server with no GEMINI_API_KEY set (e.g. nanobanana-imagen-mcp --help) does not create any files or directories.
Claude Desktop Configuration
From pip (recommended)
pip install nanobanana-imagen-mcp
{
"mcpServers": {
"nanobanana": {
"command": "uvx",
"args": ["nanobanana-imagen-mcp"],
"env": {
"GEMINI_API_KEY": "your_key_here"
}
}
}
}
From this repository
{
"mcpServers": {
"nanobanana": {
"command": "python",
"args": ["-m", "servers.nanobanana.nanobanana_mcp_server.server"],
"env": {
"GEMINI_API_KEY": "your_key_here"
},
"cwd": "path/to/gemini-media-mcp"
}
}
}
Features
- Default 4K resolution for maximum detail
- Pro model for complex, photorealistic scenes
- Flash model for fast iterations and simple subjects
- Reference image support for consistent multi-angle shots
- Negative prompt support for quality control
- Thinking level control for complex multi-element scenes
- Google Search grounding for real-world subjects
License
MIT
Credits
Inspired by the nano-banana naming convention used across the MCP community. This is an independent implementation.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.