
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.
Public tool metadata for what this MCP can expose to an agent.
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 paramsGenerate 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...
callback_urlvaluecountvaluemodelstringflux-dev · flux-pro · flux-pro-1.1 · flux-pro-1.1-ultra · flux-kontext-pro · flux-kontext-maxdefault: flux-devpromptstringsizevalueflux_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 paramsEdit 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: -...
callback_urlvalueimage_urlstringmodelstringflux-dev · flux-pro · flux-pro-1.1 · flux-pro-1.1-ultra · flux-kontext-pro · flux-kontext-maxdefault: flux-kontext-propromptstringsizevalueflux_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 paramsQuery 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...
task_idstringflux_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 paramsQuery 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...
task_idsarrayA 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. |
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.
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 mcp add --transport http --scope user flux https://flux.mcp.acedata.cloud/mcp, then claude mcp login flux. Check /mcp. Claude Code MCP guide.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.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 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"}
}
}
Bearer . An API Key / API Token field expects this raw value; only a manually configured HTTP Authorization header needs the Bearer prefix. A platform-... account-management token cannot replace a generation API key.

Save the key in the client's credential store or the environment variable shown below. Never put it in a prompt, shared workflow, screenshot, or Git commit. If authentication fails, check the full copied value, application/service access, expiration, usage limit, and balance before creating another key.
A fixed Bearer header bypasses OAuth. If the header is invalid, remove it before trying browser sign-in; keep the saved credential private.
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.
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.
https://flux.mcp.acedata.cloud/health returning {"status":"ok"} checks endpoint reachability only.flux_list_models is a reference tool; it does not verify downstream API access or balance.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.
| 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-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 |
"Generate a photorealistic mountain landscape at golden hour"
→ flux_generate_image(prompt="...", model="flux-2-max", size="16:9")
"Add sunglasses to the person in this photo"
→ flux_edit_image(prompt="Add sunglasses", image_url="https://...", size="1:1", 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.
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.
ACEDATACLOUD_API_TOKEN*secretAPI token from Ace Data Cloud (https://platform.acedata.cloud)