Nano Banana Mcp

Name: Nano Banana Mcp
Author: ConechoAI

@ConechoAI

Nano Banana Mcp について

A Model Context Protocol (MCP) server that provides AI image generation and editing capabilities using Google's Gemini 2.5 Flash Image API. Generate stunning images, edit existing ones, and iterate on your creations with simple text prompts.

#ai-image-generation #google-s-gemini-2-5-flash-image-api #nano-banana #mcp

基本情報

カテゴリ

その他

トランスポート

stdio

公開者

ConechoAI

投稿者

Bin He

設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "nano-banana": {
      "command": "npx",
      "args": [
        "nano-banana-mcp"
      ],
      "env": {
        "GEMINI_API_KEY": "your-gemini-api-key-here"
      }
    }
  }
}

ツール

Configure your Gemini API token for nano-banana image generation

Generate a NEW image from text prompt. Use this ONLY when creating a completely new image, not when modifying an existing one.

Edit a SPECIFIC existing image file, optionally using additional reference images. Use this when you have the exact file path of an image to modify.

Check if Gemini API token is configured

Continue editing the LAST image that was generated or edited in this session, optionally using additional reference images. Use this for iterative improvements, modifications, or changes to the most recent image. This automatically uses the previous image without needing a file path.

Get information about the last generated/edited image in this session (file path, size, etc.). Use this to check what image is currently available for continue_editing.

概要

What is Nano Banana Mcp?

Nano Banana Mcp is a Model Context Protocol (MCP) server that provides AI image generation and editing capabilities using Google’s Gemini 2.5 Flash Image API. It lets you create images from text prompts, edit existing images, iterate on results, and use reference images for style transfer.

How to use Nano Banana Mcp?

Configure the server with your Gemini API key via an environment variable in your MCP client config (e.g., GEMINI_API_KEY), a system environment variable, or the built-in configure_gemini_token tool. Then invoke commands such as generate_image, edit_image, continue_editing, get_last_image_info, or get_configuration_status through your MCP client (Claude Code, Cursor, or others).

Key features of Nano Banana Mcp

Generate new images from text descriptions
Edit existing images with natural language prompts
Iteratively edit the last generated/edited image
Use multiple reference images for style guidance
Cross-platform file handling for Windows, macOS, Linux
Automatic image saving with organized naming

Use cases of Nano Banana Mcp

Generate visual assets or mockups from text descriptions
Edit and refine existing images by describing changes
Apply style transfer by providing reference images
Iteratively develop a design concept through successive edits

FAQ from Nano Banana Mcp

What are the dependencies or runtime requirements?

Node.js 18.0.0 or higher and a Gemini API key from Google AI Studio are required.

How do I configure my API key?

You can set it as an environment variable in your MCP client config (recommended), as a system environment variable (GEMINI_API_KEY), or use the configure_gemini_token tool to create a local .nano-banana-config.json file.

Where are generated images saved?

Images are saved to platform-specific directories: %USERPROFILE%\Documents\nano-banana-images\ on Windows, ./generated_imgs/ on macOS/Linux, or ~/nano-banana-images/ when run from system paths.

What editing features does it support?

You can edit a specific image file with edit_image, continue editing the last generated/edited image with continue_editing, and optionally supply reference images for style transfer.

Is the API key stored securely?

The recommended method keeps the key in your MCP client’s environment config, which is contained within the MCP configuration. System environment variables and a local config file are also supported, with the config file automatically ignored by Git and NPM.

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