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.

Connect: hosted OAuth, API token, or local stdio

The hosted endpoint is https://flux.mcp.acedata.cloud/mcp. Choose one route for the MCP client:

Route	When to use it	Credential setup
Hosted OAuth	The client supports remote MCP OAuth	Add only the URL, then sign in to AceDataCloud and approve access. No token needs to be pasted into client configuration.
Hosted API token	The client cannot finish OAuth, or you need an explicit integration credential	Send an AceDataCloud API token in the `Authorization: Bearer …` header. Keep it in a local secret store or environment variable.
Local stdio	The client runs a local MCP process	Install `mcp-flux-pro` and pass `ACEDATACLOUD_API_TOKEN` to that process. It still calls the AceDataCloud API.

The hosted service advertises OAuth metadata and Dynamic Client Registration (DCR). DCR registers the client application; it is not an API key. OAuth signs you in and the client sends the resulting Bearer token; it may reuse or create an API credential for the account. Browser sign-in still requires an AceDataCloud account. The hosted service can be metered: review current service documentation and displayed pricing before a real operation. Do not configure both an OAuth login and a fixed Authorization header for the same server.

Hosted OAuth examples

Claude and Claude Desktop chat: Add a remote custom connector in Customize → Connectors → Add custom connector, enter https://flux.mcp.acedata.cloud/mcp, select sign-in, and choose Register automatically if Claude asks how to register its OAuth client. Complete consent. Claude Desktop's local claude_desktop_config.json is a separate setup. Claude connector guide.
Claude Code: claude mcp add --transport http --scope user flux https://flux.mcp.acedata.cloud/mcp, then claude mcp login flux. Check /mcp. Claude Code MCP guide.
Cursor: Add a remote server with only https://flux.mcp.acedata.cloud/mcp. For a project, merge the entry below into <project>/.cursor/mcp.json; for personal use, use ~/.cursor/mcp.json. Cursor MCP guide.
VS Code / Copilot: Run MCP: Add Server, select HTTP, enter https://flux.mcp.acedata.cloud/mcp, then finish the browser sign-in. New portable workspace configs use <project>/.mcp.json; the VS Code-specific format below uses <project>/.vscode/mcp.json or the user profile. Check MCP: List Servers. VS Code MCP setup.
Codex: codex mcp add flux --url https://flux.mcp.acedata.cloud/mcp, then codex mcp login flux. Its user settings are in ~/.codex/config.toml. Official Codex MCP guide.

Cursor project config (OAuth):

{
  "mcpServers": {
    "flux": {"url": "https://flux.mcp.acedata.cloud/mcp"}
  }
}

VS Code-specific workspace config (OAuth):

{
  "servers": {
    "flux": {"type": "http", "url": "https://flux.mcp.acedata.cloud/mcp"}
  }
}

Hosted API token

Sign in at AceDataCloud Platform, open the service page, and obtain an API credential. A fixed Bearer header is useful when your client lacks OAuth; an invalid header does not fall back to OAuth in Claude Code. The header value is sensitive, so keep it out of committed files and screenshots.

For Claude Code, the shell expands the token when you add the server; treat the saved user MCP config as a secret:

export ACEDATACLOUD_API_TOKEN='YOUR_API_TOKEN'
claude mcp add --transport http --scope user flux https://flux.mcp.acedata.cloud/mcp \
  --header "Authorization: Bearer $ACEDATACLOUD_API_TOKEN"

For a Claude Code project config, put a variable reference in <project>/.mcp.json and set that variable in the environment that launches Claude Code:

{
  "mcpServers": {
    "flux": {
      "type": "http",
      "url": "https://flux.mcp.acedata.cloud/mcp",
      "headers": {"Authorization": "Bearer ${ACEDATACLOUD_API_TOKEN}"}
    }
  }
}

Cursor uses a different environment-variable syntax in ~/.cursor/mcp.json or an uncommitted project config:

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

In VS Code, run MCP: Open User Configuration and merge this server plus its masked input; ${input:...} is for VS Code's user/workspace format and is not portable to the Agent Host .mcp.json format:

{
  "inputs": [
    {"id": "acedata-flux-token", "type": "promptString", "description": "AceDataCloud API token", "password": true}
  ],
  "servers": {
    "flux": {
      "type": "http",
      "url": "https://flux.mcp.acedata.cloud/mcp",
      "headers": {"Authorization": "Bearer ${input:acedata-flux-token}"}
    }
  }
}

For Cline, use its MCP configuration UI or CLI file ~/.cline/data/settings/cline_mcp_settings.json; its remote transport value is streamableHttp. For JetBrains AI Assistant, add a remote URL from Settings → Tools → AI Assistant → Model Context Protocol (MCP). For Zed, use a context_servers entry with the URL only for OAuth or add a local Bearer header. These clients have different configuration schemas; follow their current UI rather than copying another client's JSON. Cline · JetBrains · Zed.

Local stdio

Install the package and give the local process an API token:

python -m pip install mcp-flux-pro
export ACEDATACLOUD_API_TOKEN='YOUR_API_TOKEN'
mcp-flux-pro

For Claude Desktop local MCP, merge this entry into the file opened by its developer settings (~/Library/Application Support/Claude/claude_desktop_config.json on macOS). uvx requires uv on PATH:

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

Keep this user-level file private. Self-hosted HTTP uses mcp-flux-pro --transport http --port 8000; expose it only with suitable network and TLS controls. Local execution still calls the AceDataCloud API.

Check before using the service

https://flux.mcp.acedata.cloud/health returning {"status":"ok"} checks endpoint reachability only.
Confirm that the MCP client loads tools. flux_list_models is a reference tool; it does not verify downstream API access or balance.
If you need a full API check, call flux_generate_image with your own valid input after reviewing current service documentation and displayed pricing. If the result contains a task ID, call flux_get_task on that same ID until terminal success or failure. Do not resubmit the operation just to check progress.

For 401, check which auth route the client used and whether the token or OAuth session is valid. A 403 may mean an account permission or content moderation failure; read the returned error. Insufficient balance and downstream service failures need their own diagnosis. A listed tool or submitted task does not prove a successful result.

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.

FLUX 3 video

Use flux_generate_video with a structured request for t2v, i2v, v2v or draft_enhance. For example: {"mode":"t2v","prompt":"Waves at sunset","duration":5,"resolution":"hd","generate_audio":false}. Image mode requires keyframes; video mode requires start_video. Draft enhancement uses an owned platform draft_task_id and requires the temporary draft cache still to be available.

Video generation uses POST /flux/videos with action=generate (default) and mode=t2v/i2v/v2v/draft_enhance. Each generation mode accepts its own fields. Tools return task IDs asynchronously by default; use flux_get_task for the final video. Set async=false in the request to wait synchronously.

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