Image Generation MCP Server

What does “Image Generation” MCP Server do?

The Image Generation MCP Server is a specialized Model Context Protocol (MCP) server that provides AI assistants with image generation capabilities using the Replicate Flux model. It acts as a service layer that enables AI agents to generate images dynamically by interacting with external APIs. This server enhances development workflows by allowing AI-driven applications to request and receive custom-generated images based on text prompts or other input parameters, making it useful for a variety of creative, development, and automation tasks. Its integration with Replicate’s API allows for seamless, scalable image generation without managing underlying ML models directly.

List of Prompts

No prompt templates are explicitly mentioned in the repository.

List of Resources

No specific resources are listed or described in the repository.

List of Tools

• Image Generation Tool: Exposes functionality to generate images using the Replicate Flux model via API calls. This tool allows AI clients to submit prompts and receive generated images as output.

Use Cases of this MCP Server

• Automated Image Generation for Content Creation
  Developers or AI agents can generate unique images based on text prompts to enrich blog posts, marketing materials, or social media content without manual graphic design.
• Rapid Prototyping in Design Workflows
  Designers and product teams can quickly visualize concepts by generating images directly from textual descriptions, speeding up ideation and iteration.
• AI-Driven Illustration for Applications
  Applications can automatically generate custom illustrations, avatars, or icons on demand, enhancing user engagement and personalization.
• Enhanced Chatbot and Assistant Capabilities
  Chatbots or virtual assistants can generate images in response to user queries, making interactions more engaging and informative.
• Educational and Demonstrative Content Creation
  Teachers or educational content creators can generate visual aids and diagrams dynamically for instructional purposes.

How to set it up

Windsurf

No setup instructions for Windsurf are provided in the repository.

Claude

1. Obtain a Replicate API Token:
   Sign up or log in at Replicate to get your API token.
2. Edit Configuration File:
   • MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json
   • Windows: %APPDATA%/Claude/claude_desktop_config.json
3. Insert MCP Server Configuration:
   Add the following JSON to the mcpServers object:

   {
     "mcpServers": {
       "image-gen": {
         "command": "npx",
         "args": ["@gongrzhe/image-gen-server"],
         "env": {
           "REPLICATE_API_TOKEN": "your-replicate-api-token",
           "MODEL": "alternative-model-name"
         },
         "disabled": false,
         "autoApprove": []
       }
     }
   }
   

4. Save and Restart Claude Desktop.
5. Verify the Setup:
   Ensure the server appears and is enabled in the Claude Desktop interface.

Securing API Keys:
Store sensitive API keys (e.g., REPLICATE_API_TOKEN) in the env section of the config.

Cursor

No setup instructions for Cursor are provided in the repository.

Cline

No setup instructions for Cline are provided in the repository.

How to use this MCP inside flows

Using MCP in FlowHunt

To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:

Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:

{
  "image-gen": {
    "transport": "streamable_http",
    "url": "https://yourmcpserver.example/pathtothemcp/url"
  }
}

Once configured, the AI agent is now able to use this MCP as a tool with access to all its functions and capabilities. Remember to change "image-gen" to whatever the actual name of your MCP server is and replace the URL with your own MCP server URL.

Overview

Based on the available documentation, Image Generation MCP Server provides a focused but limited set of features (mainly image generation), with clear setup for Claude but not for other platforms. The lack of prompt and resource documentation limits its reusability, but it is functional and clearly open source.

MCP Score

Rating:
This MCP server scores around 5/10: it is functional and open-source with a clear image generation tool, but lacks breadth in prompts, resources, and multi-platform documentation, and there is no evidence of Roots or Sampling support.