ai-ml

Universal Image Generator

ecnu3d

by ecnu3d

Universal Image Generator is an AI image generator that supports multi-provider photo creation, advanced editing, and au

Provides multi-provider image generation and transformation capabilities across Google Gemini, ZhipuAI, and Alibaba Bailian with automatic prompt translation and optimization for each provider's preferred language, supporting URL-based editing with mask support and flexible input methods including base64 encoding, file paths, and public URLs.

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

3 AI providers in one serverAutomatic prompt optimization per providerNo manual installation with uvx

best for

  • / Content creators needing diverse AI image generation options
  • / Developers building applications with image generation features
  • / Users wanting to compare outputs across different AI providers
  • / Projects requiring image editing and transformation

capabilities

  • / Generate images from text prompts
  • / Edit existing images with masks
  • / Automatically translate prompts to optimal language per provider
  • / Support multiple input formats (base64, file paths, URLs)
  • / Save generated images locally
  • / Switch between Google, ZhipuAI, and Bailian providers

what it does

Generates and edits images using multiple AI providers (Google Gemini, ZhipuAI, Alibaba Bailian) with automatic prompt optimization and translation for each provider.

about

Universal Image Generator is a community-built MCP server published by ecnu3d that provides AI assistants with tools and capabilities via the Model Context Protocol. Universal Image Generator is an AI image generator that supports multi-provider photo creation, advanced editing, and au It is categorized under ai ml.

how to install

You can install Universal Image Generator 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

Universal Image Generator is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

Universal Image Generator MCP Server

PyPI version License Python versions

This project is a fork and rewrite of the original: https://github.com/qhdrl12/mcp-server-gemini-image-generator repo.

Multi-provider AI image generation server for MCP clients. Generate high-quality images using Google (Imagen & Gemini), ZHIPU AI CogView-4, or Alibaba Bailian through any MCP-compatible application.

Features

  • Multi-Provider Support: Choose between Google (Imagen/Gemini), ZhipuAI, or Bailian
  • Image Generation: Text-to-image for all providers
  • Image Transformation: Edit existing images (Google & Bailian only)
  • Smart Language Optimization: Automatic prompt translation and optimization
  • Local Storage: Save generated images to your specified directory

Quick Setup

1. Install via uvx

No manual installation required! The server will be automatically downloaded and run.

2. Get API Keys

Choose one provider and get an API key:

3. Configure MCP Client

Add to your MCP client configuration (e.g., claude_desktop_config.json):

{
    "mcpServers": {
        "universal-image-generator": {
            "command": "uvx",
            "args": [
                "universal-image-generator-mcp"
            ],
            "env": {
                "IMAGE_PROVIDER": "google",
                "GOOGLE_MODEL": "gemini",
                "ZHIPU_API_KEY": "your-api-key-here",
                "GEMINI_API_KEY": "your-api-key-here",
                "DASHSCOPE_API_KEY": "your-api-key-here",
                "OUTPUT_IMAGE_PATH": "/path/to/save/images"
            }
        }
    }
}

Environment Variables:

  • IMAGE_PROVIDER: "google", "zhipuai", or "bailian"
  • GOOGLE_MODEL: "gemini" or "imagen" (only for Google provider, defaults to "gemini")
  • Set the corresponding API key for your chosen provider
  • OUTPUT_IMAGE_PATH: Directory to save generated images (optional)

Available Tools

generate_image_from_text

Create images from text descriptions.

generate_image_from_text(prompt: str, model_type: Optional[str] = None) -> str

Parameters:

  • prompt: Text description of the image to generate
  • model_type: Optional model selection for Google provider ("gemini" or "imagen")
    • Only applies to Google provider
    • If not specified, uses GOOGLE_MODEL environment variable (defaults to "gemini")

transform_image_from_encoded (Google & Bailian only)

Transform images using base64-encoded image data.

transform_image_from_encoded(encoded_image: str, prompt: str) -> str

transform_image_from_file (Google & Bailian only)

Transform existing image files.

transform_image_from_file(image_file_path: str, prompt: str) -> str

Usage Examples

Once configured, ask your AI assistant:

  • "Generate an image of a sunset over mountains"
  • "Create a 3D rendered flying pig in a sci-fi city"
  • "Transform this image by adding snow to the scene"

Generated images are saved to your configured output directory.

Example Output

Prompt: "Create a 3D rendered image of a pig with wings and a top hat flying over a futuristic sci-fi city with lots of greenery"

Flying pig over sci-fi city

Transform: "Add a cute baby whale flying alongside the pig"

Flying pig with baby whale

Provider Capabilities

ProviderModelsGenerationTransformationLanguage Optimization
GoogleImagen, Gemini✅ (Gemini only)English prompts
ZhipuAICogView-4Chinese prompts
BailianWanX-2.1Chinese prompts

Note: For Google provider, image transformation is only supported with Gemini models. Imagen is for generation only.

Development

Test the server locally:

git clone https://github.com/ECNU3D/universal-image-generator-mcp.git
cd universal-image-generator-mcp
fastmcp dev src/universal_image_generator_mcp/server.py

Visit http://localhost:5173/ to use the MCP Inspector for testing.

License

MIT License

FAQ

What is the Universal Image Generator MCP server?
Universal Image Generator 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 Universal Image Generator?
This profile displays 32 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

4.532 reviews
  • Daniel Torres· Dec 24, 2024

    Useful MCP listing: Universal Image Generator is the kind of server we cite when onboarding engineers to host + tool permissions.

  • Jin Verma· Dec 12, 2024

    According to our notes, Universal Image Generator benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Pratham Ware· Dec 8, 2024

    I recommend Universal Image Generator for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • Harper Anderson· Nov 19, 2024

    Universal Image Generator reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

  • Aisha Jackson· Nov 15, 2024

    Universal Image Generator is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

  • Hassan Abebe· Nov 3, 2024

    Universal Image Generator has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • Jin Menon· Oct 22, 2024

    Strong directory entry: Universal Image Generator surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • Dev Ndlovu· Oct 10, 2024

    I recommend Universal Image Generator for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • Michael Bhatia· Oct 6, 2024

    Universal Image Generator is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • Yash Thakker· Sep 1, 2024

    Universal Image Generator is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

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