Summary
Connects Claude and other MCP clients to Flux AI image generation through AceDataCloud's platform. Exposes six tools for generating images from prompts, editing existing images with the Kontext model, listing available Flux models, and querying async task status. Runs as a hosted service at flux.mcp.acedata.cloud with bearer token auth, so you can use it in Claude.ai with OAuth or add it to Claude Desktop, Cursor, and VS Code with your API token. Also ships as a Python package if you want to self-host via stdio or HTTP. Good for when you need AI image generation without leaving your editor or chat interface, with support for multiple Flux model variants and batch task queries.
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Tools
Public tool metadata for what this MCP can expose to an agent.
6 tools
flux_generate_imageGenerate AI images from a text prompt using Flux. Flux is a family of fast, high-quality image generation models by Black Forest Labs. Different models offer different tradeoffs between speed, quality, and capabilities. Use this when: - You want to create new images from a tex...5 params
Generate AI images from a text prompt using Flux. Flux is a family of fast, high-quality image generation models by Black Forest Labs. Different models offer different tradeoffs between speed, quality, and capabilities. Use this when: - You want to create new images from a tex...
Parameters* required
sizevalueImage size. For flux-dev/pro/pro-1.1: pixel dimensions like '1024x1024' (256-1440px, multiples of 32). For flux-pro-1.1-ultra and kontext models: aspect ratios like '1:1', '16:9', '9:16', '4:3', '3:2', '2:3', '4:5', '5:4', '3:4', '21:9', '9:21'. Default varies by model.
countvalueNumber of images to generate. Only supported for generate action. Default is 1.
modelstringFlux model to use for generation. Options:
- flux-dev: Fast development model, good balance of speed and quality (default)
- flux-pro: Higher quality production model
- flux-pro-1.1: Improved production model with better prompt following
- flux-pro-1.1-ultra: Highest quality, supports aspect ratios instead of pixel sizes
- flux-kontext-pro: Context-aware model for editing and style transfer
- flux-kontext-max: Maximum context model for complex editing tasksone of
flux-dev · flux-pro · flux-pro-1.1 · flux-pro-1.1-ultra · flux-kontext-pro · flux-kontext-maxdefault: flux-devpromptstringDescription of the image to generate. Be descriptive about style, subject, lighting, and composition. Examples: 'A majestic mountain landscape at golden hour, photorealistic', 'Cyberpunk street scene with neon lights and rain, cinematic', 'Minimalist logo design of a phoenix, vector art style'
callback_urlvalueWebhook callback URL for asynchronous notifications. When provided, the API will POST to this URL when the image is generated.
flux_edit_imageEdit an existing image using Flux with a text prompt. This allows you to modify an existing image based on a text description. The kontext models (flux-kontext-pro, flux-kontext-max) are specifically designed for high-quality image editing and style transfer. Use this when: -...5 params
Edit an existing image using Flux with a text prompt. This allows you to modify an existing image based on a text description. The kontext models (flux-kontext-pro, flux-kontext-max) are specifically designed for high-quality image editing and style transfer. Use this when: -...
Parameters* required
sizevalueOutput image size. For kontext models: aspect ratios like '1:1', '16:9'. For other models: pixel dimensions like '1024x1024'.
modelstringFlux model to use for editing. Recommended models for editing:
- flux-kontext-pro: Best for context-aware editing and style transfer (recommended)
- flux-kontext-max: Maximum context for complex edits
- flux-dev: Basic editing support
Other models also support editing but kontext models give best results.one of
flux-dev · flux-pro · flux-pro-1.1 · flux-pro-1.1-ultra · flux-kontext-pro · flux-kontext-maxdefault: flux-kontext-propromptstringDescription of how to edit the image. Be specific about what changes to make. Examples: 'Change the background to a sunset beach', 'Add sunglasses to the person', 'Make it look like a watercolor painting', 'Replace the car with a bicycle'
image_urlstringURL of the image to edit. Must be a direct image URL (JPEG, PNG, etc.), not a web page containing an image.
callback_urlvalueWebhook callback URL for asynchronous notifications.
flux_list_modelsList all available Flux models and their capabilities. Reference guide for choosing the right Flux model for your use case. Returns: Detailed list of all Flux models with descriptions and recommendations.
List all available Flux models and their capabilities. Reference guide for choosing the right Flux model for your use case. Returns: Detailed list of all Flux models with descriptions and recommendations.
No parameter schema in public metadata yet.
flux_list_actionsList all available Flux tools and their use cases. Reference guide for what each tool does and when to use it. Returns: Categorized list of all tools with descriptions.
List all available Flux tools and their use cases. Reference guide for what each tool does and when to use it. Returns: Categorized list of all tools with descriptions.
No parameter schema in public metadata yet.
flux_get_taskQuery the status and result of a Flux image generation task. Use this to check if a generation is complete and retrieve the resulting image URLs and metadata. Use this when: - You want to check if an image generation has completed - You need to retrieve image URLs from a previ...1 params
Query the status and result of a Flux image generation task. Use this to check if a generation is complete and retrieve the resulting image URLs and metadata. Use this when: - You want to check if an image generation has completed - You need to retrieve image URLs from a previ...
Parameters* required
task_idstringThe task ID returned from a generation or edit request. This is the 'task_id' field from any flux_generate_image or flux_edit_image tool response.
flux_get_tasks_batchQuery multiple Flux image generation tasks at once. Efficiently check the status of multiple tasks in a single request. More efficient than calling flux_get_task multiple times. Use this when: - You have multiple pending generations to check - You want to get status of several...1 params
Query multiple Flux image generation tasks at once. Efficiently check the status of multiple tasks in a single request. More efficient than calling flux_get_task multiple times. Use this when: - You have multiple pending generations to check - You want to get status of several...
Parameters* required
task_idsarrayList of task IDs to query. Maximum recommended batch size is 50 tasks.
FluxMCP
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 registers the hosted 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-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
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Start earning →Configuration
ACEDATACLOUD_API_TOKEN*secretAPI token from Ace Data Cloud (https://platform.acedata.cloud)