MCP server for Flux AI image generation
Remote endpoints: streamable-http: https://flux.mcp.acedata.cloud/mcp
Valid MCP server (2 strong, 1 medium validity signals). 4 known CVEs in dependencies (0 critical, 3 high severity) Package registry verified. Imported from the Official MCP Registry.
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Set these up before or after installing:
Environment variable: ACEDATACLOUD_API_TOKEN
Available as Local & Remote
This plugin can run on your machine or connect to a hosted endpoint. during install.
From the project's GitHub README.
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.
| 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. |
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.
Connect directly on Claude.ai with OAuth — no API token needed:
https://flux.mcp.acedata.cloud/mcpAdd 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"
}
}
}
}
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"
}
}
}
}
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.
{
"mcpServers": {
"flux": {
"url": "https://flux.mcp.acedata.cloud/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_TOKEN"
}
}
}
}
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"
}
}
}
}
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"
}
}
}
}
Add to your MCP configuration:
{
"mcpServers": {
"flux": {
"type": "streamable-http",
"url": "https://flux.mcp.acedata.cloud/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_TOKEN"
}
}
}
}
Add to Roo Code MCP settings:
{
"mcpServers": {
"flux": {
"type": "streamable-http",
"url": "https://flux.mcp.acedata.cloud/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_TOKEN"
}
}
}
}
Add to .continue/config.yaml:
mcpServers:
- name: flux
type: streamable-http
url: https://flux.mcp.acedata.cloud/mcp
headers:
Authorization: "Bearer YOUR_API_TOKEN"
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"
}
}
}
}
}
# 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"}}}'
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
{
"mcpServers": {
"flux": {
"command": "uvx",
"args": ["mcp-flux-pro"],
"env": {
"ACEDATACLOUD_API_TOKEN": "your_token_here"
}
}
}
}
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.
| 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 |
| 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 |
| 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 |
"Generate a photorealistic mountain landscape at golden hour"
→ flux_generate_image(prompt="...", model="flux-pro-1.1-ultra", size="16:9")
"Add sunglasses to the person in this photo"
→ flux_edit_image(prompt="Add sunglasses", image_url="https://...", model="flux-kontext-pro")
"What's the status of my generation?"
→ flux_get_task(task_id="...")
| 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 |
git clone https://github.com/AceDataCloud/FluxMCP.git
cd FluxMCP
pip install -e ".[all]"
cp .env.example .env
# Edit .env with your API token
ruff check .
ruff format .
mypy core tools main.py
# 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 config core.hooksPath .githooks
This MCP server uses the AceDataCloud Flux API:
Full API documentation: platform.acedata.cloud
MIT License — see LICENSE for details.
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