Flux Schnell

by m-mcp

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About

Lightweight Python server using httpx for fast HTTP requests, providing a minimal configuration framework for developers seeking a quick and efficient server implementation.

Details

Author
m-mcp
Repository
m-mcp/flux-schnell-server
Categories
Design, Developer Tools, Frontend, AI, Infrastructure
Tags
#web

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

  1. Download and install Highlight from highlightai.com/download
  2. Navigate to the plugins tab and select "Add Custom Plugin"
  3. Configure the plugin with the settings below
    Plugin Name Flux Schnell
    Command (node, npx, python, etc.) npx
    Arguments
    • Argument 1 -y
    • Argument 2 @highlight/mcp-server

    Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.

  4. Enable "Start Automatically" if you want the plugin to start when Highlight launches

image_generation

Generates an image based on the provided prompt. Parameters: prompt (string), image_width (int, optional, default 512), image_height (int, optional, default 512), seed (int, optional, default 3)

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "flux schnell": {
            "env": {},
            "args": [
                "-y",
                "@highlight/mcp-server"
            ],
            "command": "npx"
        }
    }
}

Linux

{
    "env": [],
    "args": [
        "-y",
        "@highlight/mcp-server"
    ],
    "command": "npx"
}

Macos

{
    "env": [],
    "args": [
        "-y",
        "@highlight/mcp-server"
    ],
    "command": "npx"
}

Windows

{
    "env": [],
    "args": [
        "/c",
        "npx",
        "-y",
        "@highlight/mcp-server"
    ],
    "command": "cmd"
}

Flux Schnell Server

smithery badge

基于Flux Schnell模型的MCP图像生成服务器。

功能特点

- 提供基于MCP协议的图像生成API
- 支持自定义图片尺寸(宽度和高度)
- 支持设置随机种子以复现特定生成结果
- 支持异步流式响应
- 提供HTTP接口调用Hugging Face的模型服务

安装要求

- Python >= 3.10
- 依赖包:
- httpx >= 0.28.1
- mcp[cli] >= 1.3.0

使用方法

开发环境设置

1. 创建并激活 Python 虚拟环境
```bash
uv venv && source .venv/bin/activate # Unix/macOS

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