Flux MCP Integration Guide

MCP (Model Context Protocol) is a model context protocol launched by Anthropic that allows AI models (such as Claude, GPT, etc.) to call external tools through a standardized interface. With the Flux MCP Server provided by AceData Cloud, you can directly generate and edit AI images within AI clients like Claude Desktop, VS Code, Cursor, and more.

Feature Overview

Flux MCP Server offers the following core features:

Text-to-Image Generation — Generate high-quality images from text prompts
Image Editing — Edit existing images based on text instructions
Multi-Model Support — Supports various models including Flux Pro, Flux Dev, Flux Schnell, Flux Kontext, etc.
Model Query — View all available models and their capabilities
Task Query — Monitor generation progress and retrieve results

Prerequisites

Before use, you need to obtain an AceData Cloud API Token:

Register or log in to the AceData Cloud Platform
Go to the Flux Images API page
Click “Acquire” to get the API Token (free quota granted on first application)

Installation and Configuration

Method 1: pip Installation (Recommended)

pip install mcp-flux-pro

Method 2: Source Installation

git clone https://github.com/AceDataCloud/FluxMCP.git
cd FluxMCP
pip install -e .

After installation, you can start the service using the mcp-flux-pro command.

Using in Claude Desktop

Edit the Claude Desktop configuration file:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json

Add the following configuration:

{
  "mcpServers": {
    "flux": {
      "command": "mcp-flux-pro",
      "env": {
        "ACEDATACLOUD_API_TOKEN": "your API Token"
      }
    }
  }
}

If using uvx (no need to pre-install packages):

{
  "mcpServers": {
    "flux": {
      "command": "uvx",
      "args": ["mcp-flux-pro"],
      "env": {
        "ACEDATACLOUD_API_TOKEN": "your API Token"
      }
    }
  }
}

Save the configuration and restart Claude Desktop to use Flux-related tools in conversations.

Using in VS Code / Cursor

Create .vscode/mcp.json in the project root directory:

{
  "servers": {
    "flux": {
      "command": "mcp-flux-pro",
      "env": {
        "ACEDATACLOUD_API_TOKEN": "your API Token"
      }
    }
  }
}

Or use uvx:

{
  "servers": {
    "flux": {
      "command": "uvx",
      "args": ["mcp-flux-pro"],
      "env": {
        "ACEDATACLOUD_API_TOKEN": "your API Token"
      }
    }
  }
}

Available Tools

Tool Name	Description
`flux_generate_image`	Generate images from text prompts
`flux_edit_image`	Edit existing images based on text instructions
`flux_get_task`	Query the status of a single task
`flux_get_tasks_batch`	Batch query task statuses
`flux_list_models`	List all available models and their capabilities
`flux_list_actions`	List all available tools and workflow examples

Usage Examples

After configuration, you can directly invoke these features in AI clients using natural language, for example:

“Help me generate a cyberpunk-style city nightscape with Flux”
“Change the background of this photo to a beach”
“Use the Flux Kontext Pro model to edit this image and change the clothing color to red”
“List all available Flux models”

More Information

GitHub Repository: AceDataCloud/FluxMCP
PyPI Package: mcp-flux-pro
API Documentation: Flux Image Generation API

​Feature Overview

​Prerequisites

​Installation and Configuration

​Method 1: pip Installation (Recommended)

​Method 2: Source Installation

​Using in Claude Desktop

​Using in VS Code / Cursor

​Available Tools

​Usage Examples

​More Information