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 Lingxi AI Plaza, 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 Lingxi AI Plaza API Token:
- Register or log in to the Lingxi AI Plaza 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: Lingxi AI Plaza/FluxMCP
- PyPI Package: mcp-flux-pro
- API Documentation: Flux Image Generation API