FluxMCP

<!-- mcp-name: io.github.AceDataCloud/mcp-flux-pro -->

A Model Context Protocol (MCP) server for AI image generation and editing using Flux through the AceDataCloud platform.

Generate and edit stunning AI images with Flux models (flux-dev, flux-pro, flux-kontext) directly from Claude, Cursor, or any MCP-compatible client.

Features

• Image Generation - Generate images from text prompts with 6 Flux models
• Image Editing - Edit existing images with context-aware Flux Kontext models
• Task Management - Track async generation tasks and batch status queries
• Model Guide - Built-in model selection and prompt writing guidance
• Dual Transport - stdio (local) and HTTP (remote/cloud) modes
• Docker Ready - Containerized with K8s deployment manifests
• Secure - Bearer token auth with per-request isolation in HTTP mode

Tool Reference

| Tool | Description | |------|-------------| | flux_generate_image | Generate AI images from a text prompt using Flux. | | flux_edit_image | Edit an existing image using Flux with a text prompt. | | flux_list_models | List all available Flux models and their capabilities. | | flux_list_actions | List all available Flux tools and their use cases. | | flux_get_task | Query the status and result of a Flux image generation task. | | flux_get_tasks_batch | Query multiple Flux image generation tasks at once. |

Quick Start

1. Get Your API Token

1. Sign up at AceDataCloud Platform
2. Go to the API documentation page
3. Click "Acquire" to get your API token
4. Copy the token for use below

2. Use the Hosted Server (Recommended)

AceDataCloud hosts a managed MCP server — no local installation required.

Endpoint: https://flux.mcp.acedata.cloud/mcp

All requests require a Bearer token. Use the API token from Step 1.

Claude.ai

Connect directly on Claude.ai with OAuth — no API token needed:

1. Go to Claude.ai Settings → Integrations → Add More
2. Enter the server URL: https://flux.mcp.acedata.cloud/mcp
3. Complete the OAuth login flow
4. Start using the tools in your conversation

Claude Desktop

Add to your config (~/Library/Application Support/Claude/claude_desktop_config.json on macOS):

{
  "mcpServers": {
    "flux": {
      "type": "streamable-http",
      "url": "https://flux.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

Cursor / Windsurf

Add to your MCP config (.cursor/mcp.json or .windsurf/mcp.json):

{
  "mcpServers": {
    "flux": {
      "type": "streamable-http",
      "url": "https://flux.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

VS Code (Copilot)

Add to your VS Code MCP config (.vscode/mcp.json):

{
  "servers": {
    "flux": {
      "type": "streamable-http",
      "url": "https://flux.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

Or install the Ace Data Cloud MCP extension for VS Code, which registers the hosted MCP servers with one-click setup.

JetBrains IDEs

1. Go to Settings → Tools → AI Assistant → Model Context Protocol (MCP)
2. Click Add → HTTP
3. Paste:

{
  "mcpServers": {
    "flux": {
      "url": "https://flux.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

Claude Code

Claude Code supports MCP servers natively:

claude mcp add flux --transport http https://flux.mcp.acedata.cloud/mcp \
  -h "Authorization: Bearer YOUR_API_TOKEN"

Or add to your project's .mcp.json:

{
  "mcpServers": {
    "flux": {
      "type": "streamable-http",
      "url": "https://flux.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

Cline

Add to Cline's MCP settings (.cline/mcp_settings.json):

{
  "mcpServers": {
    "flux": {
      "type": "streamable-http",
      "url": "https://flux.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

Amazon Q Developer

Add to your MCP configuration:

{
  "mcpServers": {
    "flux": {
      "type": "streamable-http",
      "url": "https://flux.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

Roo Code

Add to Roo Code MCP settings:

{
  "mcpServers": {
    "flux": {
      "type": "streamable-http",
      "url": "https://flux.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

Continue.dev

Add to .continue/config.yaml:

mcpServers:
  - name: flux
    type: streamable-http
    url: https://flux.mcp.acedata.cloud/mcp
    headers:
      Authorization: "Bearer YOUR_API_TOKEN"

Zed

Add to Zed's settings (~/.config/zed/settings.json):

{
  "language_models": {
    "mcp_servers": {
      "flux": {
        "url": "https://flux.mcp.acedata.cloud/mcp",
        "headers": {
          "Authorization": "Bearer YOUR_API_TOKEN"
        }
      }
    }
  }
}

cURL Test

# Health check (no auth required)
curl https://flux.mcp.acedata.cloud/health

# MCP initialize
curl -X POST https://flux.mcp.acedata.cloud/mcp \
  -H "Content-Type: application/json" \
  -H "Accept: application/json" \
  -H "Authorization: Bearer YOUR_API_TOKEN" \
  -d '{"jsonrpc":"2.0","id":1,"method":"initialize","params":{"protocolVersion":"2025-03-26","capabilities":{},"clientInfo":{"name":"test","version":"1.0"}}}'

3. Or Run Locally (Alternative)

If you prefer to run the server on your own machine:

# Install from PyPI
pip install mcp-flux-pro
# or
uvx mcp-flux-pro

# Set your API token
export ACEDATACLOUD_API_TOKEN="your_token_here"

# Run (stdio mode for Claude Desktop / local clients)
mcp-flux-pro

# Run (HTTP mode for remote access)
mcp-flux-pro --transport http --port 8000

Claude Desktop (Local)

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

Docker (Self-Hosting)

docker pull ghcr.io/acedatacloud/mcp-flux-pro:latest
docker run -p 8000:8000 ghcr.io/acedatacloud/mcp-flux-pro:latest

Clients connect with their own Bearer token — the server extracts the token from each request's Authorization header.

Available Tools

| Tool | Description | | ---------------------- | ------------------------------------------------------ | | flux_generate_image | Generate images from text prompts with model selection | | flux_edit_image | Edit existing images with text instructions | | flux_get_task | Query status of a single generation task | | flux_get_tasks_batch | Query multiple task statuses at once | | flux_list_models | List all available Flux models and capabilities | | flux_list_actions | Show all tools and workflow examples |

Available Prompts

| Prompt | Description | | ----------------------------- | -------------------------------------------- | | flux_image_generation_guide | Guide for choosing the right tool and model | | flux_prompt_writing_guide | Best practices for writing effective prompts | | flux_workflow_examples | Common workflow patterns and examples |

Supported Models

| Model | Quality | Speed | Size Format | Best For | | ------------------ | ------- | ------ | ------------------- | ----------------------- | | flux-dev | Good | Fast | Pixels (256-1440px) | Quick prototyping | | flux-pro | High | Medium | Pixels (256-1440px) | Production use | | flux-kontext-pro | High | Medium | Aspect ratios | Image editing | | flux-kontext-max | Highest | Slower | Aspect ratios | Complex editing | | flux-2-flex | High | Fast | Aspect ratios | Flux 2 balanced quality | | flux-2-pro | Higher | Medium | Aspect ratios | Flux 2 production | | flux-2-max | Highest | Slower | Aspect ratios | Flux 2 maximum quality |

Usage Examples

Generate an Image

"Generate a photorealistic mountain landscape at golden hour"
→ flux_generate_image(prompt="...", model="flux-2-max", size="16:9")

Edit an Image

"Add sunglasses to the person in this photo"
→ flux_edit_image(prompt="Add sunglasses", image_url="https://...", model="flux-kontext-pro")

Check Task Status

"What's the status of my generation?"
→ flux_get_task(task_id="...")

Environment Variables

| Variable | Required | Default | Description | | --------------------------- | ----------- | --------------------------- | --------------------------- | | ACEDATACLOUD_API_TOKEN | Yes (stdio) | — | API token from AceDataCloud | | ACEDATACLOUD_API_BASE_URL | No | https://api.acedata.cloud | API base URL | | ACEDATACLOUD_OAUTH_CLIENT_ID | No | — | OAuth client ID (hosted mode) | | ACEDATACLOUD_PLATFORM_BASE_URL | No | https://platform.acedata.cloud | Platform base URL | | FLUX_REQUEST_TIMEOUT | No | 1800 | Request timeout in seconds | | MCP_SERVER_NAME | No | flux | MCP server name | | LOG_LEVEL | No | INFO | Logging level |

Development

Setup

git clone https://github.com/AceDataCloud/FluxMCP.git
cd FluxMCP
pip install -e ".[all]"
cp .env.example .env
# Edit .env with your API token

Lint & Format

ruff check .
ruff format .
mypy core tools main.py

Test

# Unit tests
pytest --cov=core --cov=tools

# Skip integration tests
pytest -m "not integration"

# With coverage report
pytest --cov=core --cov=tools --cov-report=html

Git Hooks

git config core.hooksPath .githooks

API Reference

This MCP server uses the AceDataCloud Flux API:

• POST /flux/images — Generate or edit images
• POST /flux/tasks — Query task status (single or batch)

Full API documentation: platform.acedata.cloud

License

MIT License — see LICENSE for details.

Links

• AceDataCloud Platform
• [MCP Protocol](https://modelc