pypi mcp-flux-prostreamable-httpMITupdated 11d ago
A Model Context Protocol (MCP) server for AI image generation and editing using Flux through the AceDataCloud platform.
mcp flux pro で何ができる?
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 |
flux-2-klein |
Good | Fast | Aspect ratios | Flux 2 efficient output |
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://...", size="1:1", 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
Documentation
License
MIT License — see LICENSE for details.
Links
インストール
mcp flux pro をクライアントに追加します。お使いのものを選んでください。
{
"servers": {
"mcp-flux-pro": {
"type": "http",
"url": "https://flux.mcp.acedata.cloud/mcp"
}
}
}Add to `.vscode/mcp.json` in your workspace.
claude mcp add mcp-flux-pro -- uvx mcp-flux-procodex mcp add mcp-flux-pro -- uvx mcp-flux-proamp mcp add mcp-flux-pro -- uvx mcp-flux-pro{
"mcpServers": {
"mcp-flux-pro": {
"command": "uvx",
"args": [
"mcp-flux-pro"
]
}
}
}Add to `claude_desktop_config.json`, then restart Claude Desktop.
{
"mcpServers": {
"mcp-flux-pro": {
"command": "uvx",
"args": [
"mcp-flux-pro"
]
}
}
}Add to `~/.cursor/mcp.json`, or `.cursor/mcp.json` for a single project.
{
"mcpServers": {
"mcp-flux-pro": {
"command": "uvx",
"args": [
"mcp-flux-pro"
]
}
}
}Add to `~/.codeium/windsurf/mcp_config.json`.
{
"mcpServers": {
"mcp-flux-pro": {
"command": "uvx",
"args": [
"mcp-flux-pro"
]
}
}
}Add to `cline_mcp_settings.json` via the MCP Servers panel.
{
"mcpServers": {
"mcp-flux-pro": {
"command": "uvx",
"args": [
"mcp-flux-pro"
]
}
}
}Add to `~/.gemini/settings.json`.
{
"mcpServers": {
"mcp-flux-pro": {
"type": "local",
"command": "uvx",
"args": [
"mcp-flux-pro"
],
"tools": [
"*"
]
}
}
}Add to `~/.copilot/mcp-config.json`, or run `/mcp add` inside the CLI.
{
"context_servers": {
"mcp-flux-pro": {
"command": {
"path": "uvx",
"args": [
"mcp-flux-pro"
]
}
}
}
}Add to your Zed `settings.json`.
uvx mcp-flux-proRun `goose configure`, choose **Add Extension → Command-line Extension**, and paste this command.
6 個のツール
mcp flux pro は接続したエージェントに 6 個のツールを提供します。
- 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.
スコア
87 / 100
優秀
- ドキュメント25/25
- メンテナンス25/25
- 信頼性16/20
- 機能6/15
- 導入のしやすさ15/15
- Documents what it does and how to connect
- Has a resolvable package or endpoint
- Exposes at least one tool, prompt or resource
- README has substantive content
- Includes a code example
- Documents its configuration
- Mentions credentials or security posture
- Last commit 4 days ago
- Has a release history
- Repository is not archived
- Licensed MIT
- Namespace verified in the official MCP registry
- Claimed by its owner
- Published under an organisation
- 6 tool(s) documented
- Provides prompt templates
- Provides resources
- 18 documented install method(s)
- Published to a package registry
- Offers a hosted endpoint — no local install
バージョン履歴
| バージョン | 公開日 |
|---|---|
| 2026.8.28.0最新 | 2026年8月28日 |
| 2026.8.23.0 | 2026年8月23日 |
| 2026.8.18.1 | 2026年8月18日 |
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