nanobanana-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| NANOBANANA_API_KEY | Yes | API key for the image generation service. | |
| NANOBANANA_BASE_URL | Yes | Base URL of the API (e.g., https://openrouter.ai/api). | |
| NANOBANANA_OUTPUT_DIR | Yes | Directory where generated images will be saved. | |
| NANOBANANA_DEFAULT_MODEL | No | Default model for image generation. | google/gemini-2.5-flash-image-preview |
| NANOBANANA_DEFAULT_IMAGE_SIZE | No | Default image size (e.g., 1K, 2K, 4K). | 1K |
| NANOBANANA_DEFAULT_ASPECT_RATIO | No | Default aspect ratio for generated images. | 1:1 |
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 | 生成 AI 图片（OpenAI 兼容协议）。 参数说明:
|
| edit_imageA | 基于参考图片生成新图片（图生图）。 参数说明:
|
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 2 tools
The two tools are clearly distinct: generate_image creates from a text prompt, while edit_image uses a reference image. Their purposes do not overlap, and the parameter differences (prompt + aspectRatio vs. prompt + referenceImageUrl) make selection unambiguous.
Both tools follow the exact same verb_noun pattern with underscores: generate_image and edit_image. This is perfectly consistent and predictable.
With only 2 tools, the server feels thin for a general image generation service, but it is tightly scoped to the two core generation workflows. It is borderline but not unreasonable for a specialized server.
The server covers the primary image generation operations: text-to-image and image-to-image editing. Minor gaps exist (e.g., no upscaling or variation tools), but for the stated purpose, the surface is mostly complete.