What can you do with this server?

MCPFlux is an MCP server for AI image generation and editing using Flux models via the AceDataCloud platform. * Generate images from text prompts using 6 Flux models (flux-dev, flux-pro, flux-pro-1.1, flux-pro-1.1-ultra, flux-kontext-pro, flux-kontext-max), with customizable sizes, aspect ratios, batch counts, and optional webhook callbacks * Edit existing images by providing an image URL and a text description of desired changes (e.g., style transfer, object replacement, background changes), with Kontext models recommended for best results * Check task status for individual generation/edit tasks, retrieving image URLs and metadata once complete * Batch query multiple tasks at once (up to 50), more efficiently than querying one at a time * List available models to get detailed descriptions, capabilities, and recommendations for each Flux model * Explore tools and guidance to get a reference of all available actions, prompt best practices, and common workflow examples * Connect from various MCP-compatible clients (Claude, Cursor, VS Code, JetBrains, etc.) via hosted HTTP server or local stdio modes, with Bearer token authentication

Which integrations are available for this server?

Provides tools for AI image generation and editing using Flux models (flux-dev, flux-pro, flux-pro-1.1, flux-pro-1.1-ultra, flux-kontext-pro, and flux-kontext-max) via the AceDataCloud platform, enabling text-to-image generation and context-aware image modification.

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FluxMCP

by AceDataCloud

Overview Schema Related Servers Score Discussions

Python

Hybrid

FluxMCP

PyPI version PyPI downloads License: MIT MCP Python 3.10+

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

Sign up at AceDataCloud Platform
Go to the API documentation page
Click "Acquire" to get your API token
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:

Go to Claude.ai Settings → Integrations → Add More
Enter the server URL: https://flux.mcp.acedata.cloud/mcp
Complete the OAuth login flow
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 bundles all 15 MCP servers with one-click setup.

JetBrains IDEs

Go to Settings → Tools → AI Assistant → Model Context Protocol (MCP)
Click Add → HTTP
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-pro-1.1`	High	Medium	Pixels (256-1440px)	Better prompt following
`flux-pro-1.1-ultra`	Highest	Slower	Aspect ratios	Maximum quality
`flux-kontext-pro`	High	Medium	Aspect ratios	Image editing
`flux-kontext-max`	Highest	Slower	Aspect ratios	Complex editing

Usage Examples

Generate an Image

"Generate a photorealistic mountain landscape at golden hour"
→ flux_generate_image(prompt="...", model="flux-pro-1.1-ultra", 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.

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FluxMCP

Features

Tool Reference

Quick Start

1. Get Your API Token

2. Use the Hosted Server (Recommended)

Claude.ai

Claude Desktop

Cursor / Windsurf

VS Code (Copilot)

JetBrains IDEs

Claude Code

Cline

Amazon Q Developer

Roo Code

Continue.dev

Zed

cURL Test

3. Or Run Locally (Alternative)

Claude Desktop (Local)

Docker (Self-Hosting)

Available Tools

Available Prompts

Supported Models

Usage Examples

Generate an Image

Edit an Image

Check Task Status

Environment Variables

Development

Setup

Lint & Format

Test

Git Hooks

API Reference

License

Links

Resources

Tools

Latest Blog Posts

MCP directory API