Skip to main content
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:
  1. Register or log in to the AceData Cloud Platform
  2. Go to the Flux Images API page
  3. Click “Acquire” to get the API Token (free quota granted on first application)

​
Installation and Configuration

pip install mcp-flux-pro

​
Method 2: Source Installation

git clone https://github.com/AceDataCloud/MCPFlux.git
cd MCPFlux
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 NameDescription
flux_generate_imageGenerate images from text prompts
flux_edit_imageEdit existing images based on text instructions
flux_get_taskQuery the status of a single task
flux_get_tasks_batchBatch query task statuses
flux_list_modelsList all available models and their capabilities
flux_list_actionsList 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