generate_imageLABSCO SUMMARY
Iteration is the feature, not generation.
Anything can generate an image from a prompt; what makes this usable is that the second request keeps the first one's context, so "same scene, different light" actually stays the same scene. The tier table is worth reading before you commit — flash is the only one that takes video, pro is the one that renders text you can read, and nano exists for volume.
What it is
An image generation and editing server over Google's Gemini image models. Each result comes back with an interaction_id, so the next instruction — heavier fog, add a deer — continues the same conversation rather than starting a new image from scratch.
What you get
generate_image— a prompt, an output path, and control overratio,sizeup to 4K, and groundingedit_image— chain fromprevious_interaction_id, or passreference_imagesfrom disk, up to 14 inputsgenerate_story— one prompt becomes a numbered sequence of captioned images: storyboards, comics, recipesgenerate_icon_set— one prompt per icon, chained so the whole set shares a lookgenerate_from_video— a poster or thumbnail from a public YouTube URLuse_searchgrounds an image in current data through Google Search;use_image_searchadds visual context- Three tiers with different capabilities —
nanoat 1K and PNG only,flashfor the widest ratios and video input,profor the highest quality and legible text inside the image - Inline previews returned to the client by default, so the model can see what it produced and correct itself
Requirements
Node.js 18+ and a Gemini API key from Google AI Studio, set as GEMINI_API_KEY. Clone, npm install, then register index.js with your client. One thing to check first: the Interactions API is in beta and the Gemini 3 tiers may need access on your key — set model: "nano" if flash or pro come back unavailable. Model IDs can be repointed per tier with NANO_BANANA_MODEL_FLASH and its siblings when Google rotates them. Version 2.1.0, MIT licensed.
Setup effort
Build from source — clone the repository, then follow the project's own run instructions
USE CASES
Getting a hero image to look right
Generate a first version, then keep editing through the interaction ID until it lands.
Producing an icon set that matches
Give one prompt per icon and let chained generation hold the style across all of them.
Turning an explanation into panels
One prompt returns interleaved captions and images, numbered into a directory.
5 tools
Listed in project docs. Your client may show a different list.
edit_imagegenerate_storygenerate_icon_setgenerate_from_videoBEFORE YOU INSTALL
What to know first
Tools you get
5 tools named in the project's documentation.
Requires
- Node.js 18+
- GEMINI_API_KEY in your environment
Where it runs
All 4 documented clients run the server on your machine.
INSTALLATION
Connect your client
Server setup
git clone https://github.com/petrkindlmann/nano-banana-mcp.git && cd nano-banana-mcp && npm installMCP Clients
Claude Code
claude mcp add nano-banana --scope user --env GEMINI_API_KEY=<YOUR_GEMINI_API_KEY> -- node <YOUR_PATH_TO_NANO_BANANA_MCP>/index.jsClaude Desktop, Cursor, Other MCP clients
{
"mcpServers": {
"nano-banana": {
"command": "node",
"args": [
"<YOUR_PATH_TO_NANO_BANANA_MCP>/index.js"
],
"env": {
"GEMINI_API_KEY": "<YOUR_GEMINI_API_KEY>"
}
}
}
}