Cover image
GongRzhe_Image-Generation-MCP-Server
Public

GongRzhe_Image-Generation-MCP-Server

Try Now
2025-03-11

Mirror ofhttps://github.com/GongRzhe/Image-Generation-MCP-Server

3 years

Works with Finder

0

Github Watches

1

Github Forks

0

Github Stars

Image Generation MCP Server

This MCP server provides image generation capabilities using the Replicate Flux model.

Setup

  1. On MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json On Windows: %APPDATA%/Claude/claude_desktop_config.json
{
  "mcpServers": {
    "image-gen": {
      "command": "node",
      "args": ["/path/to/image-gen-server/build/index.js"],
      "env": {
        "REPLICATE_API_TOKEN": "your-replicate-api-token",
        "MODEL": "alternative-model-name"
      },
      "disabled": false,
      "autoApprove": []
    }
  }
}
  1. Get your Replicate API token:

image

Environment Variables

  • REPLICATE_API_TOKEN (required): Your Replicate API token for authentication
  • MODEL (optional): The Replicate model to use for image generation. Defaults to "black-forest-labs/flux-schnell"

Configuration Parameters

  • disabled: Controls whether the server is enabled (false) or disabled (true)
  • autoApprove: Array of tool names that can be executed without user confirmation. Empty array means all tool calls require confirmation.

Available Tools

generate_image

Generates images using the Flux model based on text prompts.

image

out-0 (1)

Parameters

  • prompt (required): Text description of the image to generate
  • seed (optional): Random seed for reproducible generation
  • aspect_ratio (optional): Image aspect ratio (default: "1:1")
  • output_format (optional): Output format - "webp", "jpg", or "png" (default: "webp")
  • num_outputs (optional): Number of images to generate (1-4, default: 1)

Example Usage

const result = await use_mcp_tool({
  server_name: "image-gen",
  tool_name: "generate_image",
  arguments: {
    prompt: "A beautiful sunset over mountains",
    aspect_ratio: "16:9",
    output_format: "png",
    num_outputs: 1
  }
});

The tool returns an array of URLs to the generated images.

📜 License

This project is licensed under the MIT License.

相关推荐

  • NiKole Maxwell
  • I craft unique cereal names, stories, and ridiculously cute Cereal Baby images.

  • Bora Yalcin
  • Evaluator for marketplace product descriptions, checks for relevancy and keyword stuffing.

  • Joshua Armstrong
  • Confidential guide on numerology and astrology, based of GG33 Public information

  • https://suefel.com
  • Latest advice and best practices for custom GPT development.

  • Emmet Halm
  • Converts Figma frames into front-end code for various mobile frameworks.

  • Elijah Ng Shi Yi
  • Advanced software engineer GPT that excels through nailing the basics.

  • https://maiplestudio.com
  • Find Exhibitors, Speakers and more

  • Lists Tailwind CSS classes in monospaced font

  • Beniyam Berhanu
  • Therapist adept at identifying core issues and offering practical advice with images.

  • lumpenspace
  • Take an adjectivised noun, and create images making it progressively more adjective!

  • apappascs
  • Discover the most comprehensive and up-to-date collection of MCP servers in the market. This repository serves as a centralized hub, offering an extensive catalog of open-source and proprietary MCP servers, complete with features, documentation links, and contributors.

  • ShrimpingIt
  • Micropython I2C-based manipulation of the MCP series GPIO expander, derived from Adafruit_MCP230xx

  • huahuayu
  • A unified API gateway for integrating multiple etherscan-like blockchain explorer APIs with Model Context Protocol (MCP) support for AI assistants.

  • deemkeen
  • control your mbot2 with a power combo: mqtt+mcp+llm

  • jae-jae
  • MCP server for fetch web page content using Playwright headless browser.

    Reviews

    3 (1)
    Avatar
    user_7sH9AIhS
    2025-04-16

    As a dedicated user of the GongRzhe_Image-Generation-MCP-Server by MCP-Mirror, I must say it's an outstanding tool for image generation. The seamless integration and efficient performance have significantly enhanced my workflow. The GitHub repository is well-maintained and the community support is impressive. Highly recommended for anyone looking into advanced image generation solutions.