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Nano Banana Pro

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Enables Claude to generate and edit images using Google's Gemini image models, with options for resolution and batch processing, and optional Firebase Storage f

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About

Enables Claude to generate and edit images using Google's Gemini image models, with options for resolution and batch processing, and optional Firebase Storage for cross-environment image transfer.

README

A minimal, auditable MCP server that gives Claude Desktop the ability to generate and edit images using Google's Nano Banana Pro (Gemini 3 Pro Image) model.

~150 lines of TypeScript. No hidden dependencies. You own the code.

What it does

Tool Description
set_model Switch between Gemini image models
set_resolution Set source resolution (1K/2K/4K)
generate_image Create an image from a text prompt
generate_image_batch Create several images at once
edit_image Edit an image (given its URL) with instructions

Generated images are returned inline (so Claude can display them in chat) and saved to ~/nano-banana-output/.

Images are never written to local disk. Each is returned inline for viewing, and — when Firebase Storage is configured — uploaded there with a signed URL you can fetch from other environments (e.g. to embed in a document).

Prerequisites

  • Node.js 18+ — check with node --version
  • Gemini API key — free from Google AI Studio. Enable billing for image generation (pay-per-image, no monthly minimum).

Setup

1. Clone and build

git clone <your-repo-url> nano-banana-mcp
cd nano-banana-mcp
npm install
npm run build

2. Configure Claude Desktop

Open your Claude Desktop config file:

  • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
  • Windows: %APPDATA%\Claude\claude_desktop_config.json

Add this entry (adjust the path to where you cloned the repo):

{
  "mcpServers": {
    "nano-banana-pro": {
      "command": "node",
      "args": ["/absolute/path/to/nano-banana-mcp/build/index.js"],
      "env": {
        "GEMINI_API_KEY": "your-api-key-here"
      }
    }
  }
}

3. Restart Claude Desktop

The server should appear in the MCP tools menu (hammer icon).

Usage examples

Once connected, just ask Claude naturally:

  • "Generate an image of a Senegalese market at sunset"
  • "Create a 16:9 hero banner for a blog about climate resilience"
  • "Edit ~/nano-banana-output/gen_20260714_a1b2.png — remove the background and add a gradient"

Models

The server supports two Gemini image models:

Model ID Quality Speed Cost
Nano Banana Pro gemini-3-pro-image-preview Highest Slower ~$0.09/image
Nano Banana gemini-2.5-flash-image Good Fast ~$0.04/image

By default, generate_image uses Pro. Pass use_pro: false to switch to the faster Flash model.

Security notes

  • Your API key stays local — it's passed via environment variable, never logged or transmitted elsewhere.
  • The server only makes HTTPS calls to generativelanguage.googleapis.com (Google's Gemini API).
  • No telemetry, no analytics, no third-party calls.
  • All code is in src/index.ts — read it before you run it.

Project structure

nano-banana-mcp/
├── src/
│   └── index.ts      ← the entire server (~150 lines)
├── package.json
├── tsconfig.json
└── README.md

License

MIT — do whatever you want with it.

Optional: Firebase Storage (cross-environment image transfer)

By default, generated images are saved to ~/nano-banana-output/ on the machine running the MCP server. If you want images to be usable in another environment (e.g. embedding in a document built by Claude's sandbox) without manually attaching files, configure Firebase Storage. The server will upload each image and return a time-limited signed URL that the other environment can download directly.

Point at your service-account JSON key file (recommended):

"env": {
  "GEMINI_API_KEY": "[API_KEY]",
  "SERVICE_ACCOUNT_KEY_PATH": "/absolute/path/to/firebase-service-account.json",
  "FIREBASE_STORAGE_BUCKET": "your-project.appspot.com"
}

Download the JSON key from Firebase Console → Project Settings → Service Accounts → Generate new private key, save it somewhere on your machine, and point SERVICE_ACCOUNT_KEY_PATH at it.

Alternatively, supply the individual fields instead of a key file (FIREBASE_PROJECT_ID, FIREBASE_CLIENT_EMAIL, FIREBASE_PRIVATE_KEY, plus FIREBASE_STORAGE_BUCKET).

Optional: FIREBASE_SIGNED_URL_MINUTES (default 60) controls how long the download URL stays valid.

Notes:

  • The service-account credentials stay in the MCP server process only — they are never sent to Claude or its sandbox. The sandbox only ever sees a plain signed URL.
  • Get the service-account values from Firebase Console → Project Settings → Service Accounts → Generate new private key.
  • If any of the four vars is missing, uploads stay disabled and the server falls back to saving locally.
  • For the download to work, the environment fetching the URL must have outbound network access to storage.googleapis.com.

from github.com/IDinsight/nano-banana-mcp

Install Nano Banana Pro in Claude Desktop, Claude Code & Cursor

Recommended · one command, every IDE
unyly install nano-banana-pro-mcp

Installs into Claude Desktop, Claude Code, Cursor & VS Code — handles npx, uvx and build-from-source repos for you.

First time? Get the CLI: curl -fsSL https://unyly.org/install | sh

Or configure manually

Run in your terminal:

claude mcp add nano-banana-pro-mcp -- npx -y nano-banana-pro-mcp

FAQ

Is Nano Banana Pro MCP free?

Yes, Nano Banana Pro MCP is free — one-click install via Unyly at no cost.

Does Nano Banana Pro need an API key?

No, Nano Banana Pro runs without API keys or environment variables.

Is Nano Banana Pro hosted or self-hosted?

Self-hosted: the server runs locally on your machine via the install command above.

How do I install Nano Banana Pro in Claude Desktop, Claude Code or Cursor?

Open Nano Banana Pro on unyly.org, pick your client tab (Claude Desktop, Claude Code, Cursor) and press Install — the config is generated automatically, no JSON editing.

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