Nano Banana Pro MCP Server
Brings Google Gemini 2.0 Flash native image generation capabilities into Claude Code, enabling users to generate, edit, compose, and iteratively refine images using natural language prompts directly from their coding environment.
README
Nano Banana Pro MCP Server
An MCP (Model Context Protocol) server that brings Google Gemini 2.0 Flash native image generation capabilities directly into Claude Code and other MCP-compatible AI assistants.
Generate, edit, and compose images using natural language - all without leaving your coding environment.
Features
- Generate Images: Create high-quality images from text prompts (up to 4K resolution)
- Edit Images: Modify existing images with text instructions
- Continue Editing: Iteratively refine the last generated image
- Compose Images: Combine up to 14 reference images into new compositions
- Google Search Grounding: Generate images based on real-time information
- Multiple Aspect Ratios: Support for 1:1, 16:9, 9:16, 4:3, 3:4, and more
- High Resolution: Output at 1K, 2K, or 4K resolution
Prerequisites
- Docker Desktop installed and running
- Gemini API key from Google AI Studio
Quick Start
1. Build the Docker Image
cd nano-banana-pro-mcp
docker build -t nano-banana-pro-mcp .
2. Create Output Directory
mkdir -p output input
3. Add to Claude Code
Add the MCP server to Claude Code using one of these methods:
Option A: Using claude mcp add (Recommended)
claude mcp add nano-banana-pro \
--transport stdio \
-- docker run -i --rm \
-e GEMINI_API_KEY=$GEMINI_API_KEY \
-v $(pwd)/output:/output \
-v $(pwd)/input:/input:ro \
nano-banana-pro-mcp
Option B: Manual Configuration
Add to your Claude Code MCP configuration file (~/.claude/claude_desktop_config.json or similar):
{
"mcpServers": {
"nano-banana-pro": {
"command": "docker",
"args": [
"run", "-i", "--rm",
"-e", "GEMINI_API_KEY",
"-v", "/path/to/output:/output",
"-v", "/path/to/input:/input:ro",
"nano-banana-pro-mcp"
],
"env": {
"GEMINI_API_KEY": "your-api-key-here"
}
}
}
}
Available Tools
generate_image
Generate a new image from a text prompt.
Parameters:
prompt(required): Text description of the image to createaspectRatio(optional): 1:1, 2:3, 3:2, 3:4, 4:3, 4:5, 5:4, 9:16, 16:9, 21:9resolution(optional): 1K, 2K, or 4KuseGoogleSearch(optional): Enable real-time information grounding
Example:
Generate a professional hero image for a tech startup website, showing a
modern office with developers collaborating, 16:9 aspect ratio, 2K resolution
edit_image
Edit an existing image with text instructions.
Parameters:
imagePath(required): Path to the image fileprompt(required): Description of the modificationsreferenceImages(optional): Array of reference image pathsaspectRatio(optional): Output aspect ratioresolution(optional): Output resolution
Example:
Edit /input/logo.png - Change the background color to gradient blue and
add a subtle glow effect around the text
continue_editing
Continue editing the last generated/edited image.
Parameters:
prompt(required): Description of additional modificationsreferenceImages(optional): Reference images for style transfer, etc.aspectRatio(optional): Output aspect ratioresolution(optional): Output resolution
Example:
Make the colors more vibrant and add a subtle drop shadow
compose_images
Combine multiple images into a new composition.
Parameters:
images(required): Array of image paths (up to 14)prompt(required): How to combine the imagesaspectRatio(optional): Output aspect ratioresolution(optional): Output resolution
Example:
Compose these product photos into a professional catalog layout
with consistent lighting and white background
get_last_image_info
Get information about the last generated image.
get_configuration_status
Check if the API key is configured.
Tips for Best Results
- Be Descriptive: The more detail in your prompt, the better the result
- Use Photography Terms: For realistic images, mention camera angles, lens types, lighting
- Iterate: Use
continue_editingto refine images step by step - Reference Images: Use up to 14 reference images for character consistency or style transfer
- Google Search: Enable for real-time data like weather, news, or current events
Output Location
Generated images are saved to the /output directory (mounted from ./output on your host).
Troubleshooting
"GEMINI_API_KEY not set"
Make sure your API key is set in your environment:
export GEMINI_API_KEY="your-key-here"
Images not appearing
Check the ./output directory on your host machine. Ensure the volume mount is correct.
Docker permission issues
On Linux, you may need to run:
sudo chown -R $USER:$USER output
Development
To run locally without Docker:
npm install
npm run build
GEMINI_API_KEY=your-key OUTPUT_DIR=./output npm start
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
License
MIT
Acknowledgments
- Google Gemini for the image generation API
- Model Context Protocol by Anthropic
- Claude Code for the amazing AI coding assistant
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。