ai-ml

Nano-Banana (Gemini 2.5 Flash Image)

conechoai

by conechoai

Generate and edit images from text with Nano-Banana, an AI image generator powered by Gemini 2.5 Flash. Fast, seamless,

Integrates with Google's Gemini 2.5 Flash to generate and edit images from text prompts, supporting iterative workflows with reference images and automatic cross-platform file management.

github stars

112

0 commentsdiscussion

Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.

Cross-platform file managementMultiple reference image supportIterative editing workflows

best for

  • / Content creators needing quick image generation
  • / Iterative design workflows and prototyping
  • / AI-assisted image editing and modifications

capabilities

  • / Generate images from text descriptions
  • / Edit existing images with text prompts
  • / Continue iterative editing on previous images
  • / Use reference images for style transfer
  • / Save images automatically with organized naming

what it does

Connects to Google's Gemini 2.5 Flash API to generate and edit images from text prompts. Supports iterative editing workflows and automatically saves images with organized file management.

about

Nano-Banana (Gemini 2.5 Flash Image) is a community-built MCP server published by conechoai that provides AI assistants with tools and capabilities via the Model Context Protocol. Generate and edit images from text with Nano-Banana, an AI image generator powered by Gemini 2.5 Flash. Fast, seamless, It is categorized under ai ml.

how to install

You can install Nano-Banana (Gemini 2.5 Flash Image) in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

license

MIT

Nano-Banana (Gemini 2.5 Flash Image) is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

Nano-Banana MCP Server 🍌

🤖 This project was entirely generated by Claude Code - an AI coding assistant that can create complete, production-ready applications from scratch.

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.

<a href="https://glama.ai/mcp/servers/@ConechoAI/Nano-Banana-MCP"> <img width="380" height="200" src="https://glama.ai/mcp/servers/@ConechoAI/Nano-Banana-MCP/badge" alt="Nano-Banana-MCP MCP server" /> </a>

✨ Features

  • 🎨 Generate Images: Create new images from text descriptions
  • ✏️ Edit Images: Modify existing images with text prompts
  • 🔄 Iterative Editing: Continue editing the last generated/edited image
  • 🖼️ Multiple Reference Images: Use reference images for style transfer and guidance
  • 🌍 Cross-Platform: Smart file paths for Windows, macOS, and Linux
  • 🔧 Easy Setup: Simple configuration with API key
  • 📁 Auto File Management: Automatic image saving with organized naming

🔑 Setup

  1. Get your Gemini API key:

  2. Configure the MCP server: See configuration examples for your specific client below (Claude Code, Cursor, or other MCP clients).

💻 Usage with Claude Code

Configuration:

Add this to your Claude Code MCP settings:

Option A: With environment variable (Recommended - Most Secure)

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

Option B: Without environment variable

{
  "mcpServers": {
    "nano-banana": {
      "command": "npx",
      "args": ["nano-banana-mcp"]
    }
  }
}

Usage Examples:

Generate an image of a sunset over mountains
Edit this image to add some birds in the sky
Continue editing to make it more dramatic

🎯 Usage with Cursor

Configuration:

Add to your Cursor MCP configuration:

Option A: With environment variable (Recommended)

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

Option B: Without environment variable

{
  "nano-banana": {
    "command": "npx",
    "args": ["nano-banana-mcp"]
  }
}

Usage Examples:

  • Ask Cursor to generate images for your app
  • Create mockups and prototypes
  • Generate assets for your projects

🔧 For Other MCP Clients

If you're using a different MCP client, you can configure nano-banana-mcp using any of these methods:

Configuration Methods

Method A: Environment Variable in MCP Config (Recommended)

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

Method B: System Environment Variable

export GEMINI_API_KEY="your-gemini-api-key-here"
npx nano-banana-mcp

Method C: Using the Configure Tool

npx nano-banana-mcp
# The server will prompt you to configure when first used
# This creates a local .nano-banana-config.json file

🛠️ Available Commands

generate_image

Create a new image from a text prompt.

generate_image({
  prompt: "A futuristic city at night with neon lights"
})

edit_image

Edit a specific image file.

edit_image({
  imagePath: "/path/to/image.png",
  prompt: "Add a rainbow in the sky",
  referenceImages?: ["/path/to/reference.jpg"] // optional
})

continue_editing

Continue editing the last generated/edited image.

continue_editing({
  prompt: "Make it more colorful",
  referenceImages?: ["/path/to/style.jpg"] // optional
})

get_last_image_info

Get information about the last generated image.

get_last_image_info()

configure_gemini_token

Configure your Gemini API key.

configure_gemini_token({
  apiKey: "your-gemini-api-key"
})

get_configuration_status

Check if the API key is configured.

get_configuration_status()

⚙️ Configuration Priority

The MCP server loads your API key in the following priority order:

  1. 🥇 MCP Configuration Environment Variables (Highest Priority)

    • Set in your claude_desktop_config.json or MCP client config
    • Most secure as it's contained within the MCP configuration
    • Example: "env": { "GEMINI_API_KEY": "your-key" }
  2. 🥈 System Environment Variables

    • Set in your shell/system environment
    • Example: export GEMINI_API_KEY="your-key"
  3. 🥉 Local Configuration File (Lowest Priority)

    • Created when using the configure_gemini_token tool
    • Stored as .nano-banana-config.json in current directory
    • Automatically ignored by Git and NPM

💡 Recommendation: Use Method 1 (MCP config env variables) for the best security and convenience.

📁 File Storage

Images are automatically saved to platform-appropriate locations:

  • Windows: %USERPROFILE%\Documents\ ano-banana-images\
  • macOS/Linux: ./generated_imgs/ (in current directory)
  • System directories: ~/nano-banana-images/ (when run from system paths)

File naming convention:

  • Generated images: generated-[timestamp]-[id].png
  • Edited images: edited-[timestamp]-[id].png

🎨 Example Workflows

Basic Image Generation

  1. generate_image - Create your base image
  2. continue_editing - Refine and improve
  3. continue_editing - Add final touches

Style Transfer

  1. generate_image - Create base content
  2. edit_image - Use reference images for style
  3. continue_editing - Fine-tune the result

Iterative Design

  1. generate_image - Start with a concept
  2. get_last_image_info - Check current state
  3. continue_editing - Make adjustments
  4. Repeat until satisfied

🔧 Development

This project was created with Claude Code and follows these technologies:

  • TypeScript - Type-safe development
  • Node.js - Runtime environment
  • Zod - Schema validation
  • Google GenAI - Image generation API
  • MCP SDK - Model Context Protocol

Local Development

# Clone the repository
git clone https://github.com/claude-code/nano-banana-mcp.git
cd nano-banana-mcp

# Install dependencies
npm install

# Run in development mode
npm run dev

# Build for production
npm run build

# Run tests
npm test

📋 Requirements

  • Node.js 18.0.0 or higher
  • Gemini API key from Google AI Studio
  • Compatible with Claude Code, Cursor, and other MCP clients

🤝 Contributing

This project was generated by Claude Code, but contributions are welcome! Please feel free to:

  • Report bugs
  • Suggest new features
  • Submit pull requests
  • Improve documentation

📄 License

MIT License - see LICENSE file for details.

🙏 Acknowledgments

  • Claude Code - For generating this entire project
  • Google AI - For the powerful Gemini 2.5 Flash Image API
  • Anthropic - For the Model Context Protocol
  • Open Source Community - For the amazing tools and libraries

📞 Support


✨ Generated with love by Claude Code - The future of AI-powered development is here!

FAQ

What is the Nano-Banana (Gemini 2.5 Flash Image) MCP server?
Nano-Banana (Gemini 2.5 Flash Image) is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?
Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for Nano-Banana (Gemini 2.5 Flash Image)?
This profile displays 36 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.5 out of 5—verify behavior in your own environment before production use.

Use Cases

Extended AI Capabilities

Add new capabilities to Claude beyond text generation

Example

Access external data sources, execute code, interact with tools and services

Transform Claude from chatbot to action-taking agent

Context Enhancement

Provide Claude with access to relevant context and data

Example

Load project documentation, access knowledge bases, query databases

Get more accurate, context-aware responses

Workflow Automation

Automate multi-step workflows combining AI and external tools

Example

Research → Summarize → Create document → Send notification

Complete complex tasks end-to-end without manual steps

Implementation Guide

Prerequisites

  • Claude Desktop 0.7.0+ or Cursor IDE with MCP support
  • Basic understanding of MCP architecture and capabilities
  • Access credentials for integrated services (if required)
  • Willingness to experiment and iterate on configuration

Time Estimate

15-60 minutes depending on server complexity

Installation Steps

  1. 1.Install MCP server: npm install -g [package-name] or via GitHub
  2. 2.Add server configuration to ~/.claude/mcp.json
  3. 3.Provide required credentials and configuration
  4. 4.Restart Claude Desktop to load new server
  5. 5.Test basic functionality with simple prompts
  6. 6.Explore capabilities and experiment with use cases
  7. 7.Document successful patterns for reuse

Troubleshooting

  • MCP server not loading: Check config syntax, verify installation
  • Connection errors: Check network, firewall, credentials
  • Feature not working: Read server docs, check required parameters
  • Performance issues: Monitor resource usage, check for network latency
  • Conflicts with other servers: Check port assignments, namespace collisions

Best Practices

✓ Do

  • +Read server documentation thoroughly before setup
  • +Start with simple use cases to validate functionality
  • +Test in non-production environment first
  • +Monitor resource usage and performance
  • +Keep servers updated for bug fixes and new features
  • +Document configuration for team members
  • +Use environment variables for sensitive configuration

✗ Don't

  • Don't grant overly permissive access to MCP servers
  • Don't skip reading security considerations in docs
  • Don't expose sensitive data without proper controls
  • Don't run untrusted MCP servers without code review
  • Don't ignore error messages—investigate root cause

💡 Pro Tips

  • Combine multiple MCP servers for powerful workflows
  • Create custom MCP servers for your specific needs
  • Share successful configurations with team
  • Use MCP inspector for debugging
  • Join MCP community for tips and troubleshooting

Technical Details

Architecture

Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.

Protocols

  • Model Context Protocol (MCP)
  • JSON-RPC 2.0
  • stdio or HTTP transport

Compatibility

  • Claude Desktop
  • Cursor IDE
  • Custom MCP clients

When to Use This

✓ Use When

Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.

✗ Avoid When

Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.

Integration

  • Tool composition: Chain multiple MCP tools in workflows
  • Context augmentation: Provide AI with relevant external data
  • Action delegation: Let AI execute tasks on external systems
  • Bidirectional sync: Keep AI context and external systems in sync

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.

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Ratings

4.536 reviews
  • Li White· Dec 16, 2024

    Nano-Banana (Gemini 2.5 Flash Image) has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • Dhruvi Jain· Dec 8, 2024

    I recommend Nano-Banana (Gemini 2.5 Flash Image) for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • Kabir Farah· Dec 8, 2024

    Strong directory entry: Nano-Banana (Gemini 2.5 Flash Image) surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • Oshnikdeep· Nov 27, 2024

    Nano-Banana (Gemini 2.5 Flash Image) is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

  • Nia Chen· Nov 27, 2024

    Nano-Banana (Gemini 2.5 Flash Image) is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • Meera Srinivasan· Nov 7, 2024

    According to our notes, Nano-Banana (Gemini 2.5 Flash Image) benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Hassan Dixit· Oct 26, 2024

    I recommend Nano-Banana (Gemini 2.5 Flash Image) for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • Ganesh Mohane· Oct 18, 2024

    Nano-Banana (Gemini 2.5 Flash Image) has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • Ishan Mensah· Oct 18, 2024

    Nano-Banana (Gemini 2.5 Flash Image) reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

  • Sakshi Patil· Sep 25, 2024

    Nano-Banana (Gemini 2.5 Flash Image) reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

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