nanobanana-imagen-mcp 1.1.1

MCP server for AI image generation using NanoBanana Pro 2 -- 4K resolution

NanoBanana 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.