nano-banana-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| OUTPUT_DIR | No | Directory for saved images | ~/nano-banana-output |
| GEMINI_MODEL | No | Gemini model for image generation/editing | gemini-3.1-flash-image-preview |
| GEMINI_API_KEY | Yes | Your Google AI API key | |
| GEMINI_BASE_URL | No | Custom base URL for Gemini API (proxy support) | |
| GEMINI_DESCRIBE_MODEL | No | Gemini model for image description (text-only output) | gemini-2.5-flash |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| generate_imageA | Generate an image from a text prompt using Google Gemini. Default model: gemini-3.1-flash-image-preview. Supports batch generation (n=1-4). Response contains a thumbnail preview; full-res image is saved to /root/nano-banana-output. |
| edit_imageA | Edit an existing image based on a text instruction using Google Gemini. Default model: gemini-3.1-flash-image-preview. Supports multi-image input (up to 10 total). Response contains a thumbnail preview; full-res image is saved to /root/nano-banana-output. |
| describe_imageA | Get a text description of an image using Google Gemini. Default model: gemini-2.5-flash. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 3 tools
Each tool has a clearly distinct purpose: generating a new image, editing an existing image, and describing an image. There is no overlap or ambiguity between them.
All tool names follow the consistent verb_noun pattern: generate_image, edit_image, describe_image. This makes the set highly predictable and easy to navigate.
With 3 tools, the server is well-scoped for its purpose of image generation, editing, and analysis. Each tool earns its place and the count is appropriate for the domain.
The tool surface covers the core lifecycle of image handling: create (generate), modify (edit), and understand (describe). There are no obvious gaps for the stated purpose.