Mcp Flux Pro

io.github.AceDataCloudPublished by GitHub account AceDataCloudv2026.11.7.0Updated Nov 7, 2026

MCP server for Flux AI image generation

VerifiedStreamable HTTPWeb executableMedia & DesignAI & ML

Overview

AI-generated overview

MCP server that lets an assistant generate and edit images and videos with Flux models through the AceDataCloud platform.

What you can do
  • Generate images from text prompts with a choice of Flux models
  • Edit existing images with text instructions using Kontext models
  • Generate FLUX 3 videos or enhance an owned draft
  • Check single or batch generation task status
  • List available models and tools, with built-in prompt and workflow guidance
When to use it
Useful when you want an assistant to create or modify images or short videos from prompts without leaving the chat client, and to poll the resulting asynchronous tasks.
Requirements
Either the hosted endpoint with OAuth sign-in to an AceDataCloud account, or a local process from the PyPI package mcp-flux-pro run with uvx or pip, which needs ACEDATACLOUD_API_TOKEN. A hosted API-token route sends the token as a Bearer Authorization header. Network access to the AceDataCloud API is required in all routes.
Before you install
Generation is a paid, metered operation on AceDataCloud; review current pricing and balance before generating, and do not retry paid operations automatically. The API token is a secret: keep it in a credential store or environment variable, never in prompts, shared configs or commits, and do not configure both OAuth and a fixed Authorization header. Local execution still sends requests to the third-party API.

Installation

In SourceWeft

  1. Open Mcp Flux Pro in the dashboard and add it to a workspace.
  2. Connect the required credentials. They are stored privately and never shown on public pages.
  3. Enable the server for the chats that should use its tools.

Web executable via Streamable HTTP. Remote servers run from the web runtime once configured in a workspace.

Use with an agent

Paste this prompt into Claude Code, Codex, Cursor or another agent — or into SourceWeft chat. The agent reads this server's install guide, shows you its publisher, endpoint and sign-in, and adds it to your client once you agree. Keys never go into a command.

Read https://sourceweft.com/mcp/io.github.AceDataCloud%2Fmcp-flux-pro/install.md and connect the MCP server it describes to my client. Before changing any config, show me its publisher, endpoint and sign-in method and wait for my OK. Never put an API key in a command or in a file I would commit; ask me where it should come from.

Read the install guide the agent follows

Other MCP clients

Add this to your client's mcpServers config. The client completes OAuth sign-in on first connect.

{
  "mcpServers": {
    "flux-pro": {
      "type": "http",
      "url": "https://flux.mcp.acedata.cloud/mcp"
    }
  }
}

README

FluxMCP

[PyPI version] [PyPI downloads] [CI] [License: MIT] [MCP] [Python 3.10+]

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 8 Flux image 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

ToolDescription
flux_generate_imageGenerate AI images from a text prompt using Flux.
flux_edit_imageEdit an existing image using Flux with a text prompt.
flux_list_modelsList all available Flux models and their capabilities.
flux_list_actionsList all available Flux tools and their use cases.
flux_generate_videoGenerate FLUX 3 videos or enhance an owned draft.
flux_get_taskQuery the status and result of a Flux image generation task.
flux_get_tasks_batchQuery multiple Flux image generation tasks at once.

Verify the connection before generating

After installation, discover the server's tools and call flux_list_models with no arguments. This reference tool returns locally defined model or action information without calling a generation API. It does not validate your application key, account balance, service access, or current price. Your client's Chat model can still create separate charges.

To check authenticated access without creating media, query a task already owned by your application using the task-lookup tool and the same original task ID. If you have no existing task, stop after discovery/reference output; do not generate media just to test installation. Review current pricing before any new generation.

For missing tools, reconnect and refresh the tool list. For 401/403, check the existing application's key, service permissions, Allowed APIs, expiration and usage limit before replacing credentials. Keep a task/trace ID for other failures, never your key; do not automatically retry a paid operation.

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:

RouteWhen to use itCredential setup
Hosted OAuthThe client supports remote MCP OAuthAdd only the URL, then sign in to AceDataCloud and approve access. No token needs to be pasted into client configuration.
Hosted API tokenThe client cannot finish OAuth, or you need an explicit integration credentialSend an AceDataCloud API token in the Authorization: Bearer … header. Keep it in a local secret store or environment variable.
Local stdioThe client runs a local MCP processInstall 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):

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

VS Code-specific workspace config (OAuth):

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

Hosted API token

  1. Open Ace Data Cloud → Applications. Sign in, or register an account first.
  2. Find General application. If it has not been created, choose Initialize General Application. A general key can use the services available to your account; a dedicated application's key is limited to its service. Check the required service/model access and current pricing.
  3. Copy the API Key from the application card, or open Keys / Manage Keys → Create to create a separate key for this integration. Give it a recognizable name so you can revoke or rotate it independently.
  4. When creating a key, review Expiration Time, Set Usage Limitation, and Allowed APIs. Enable only the restrictions you need, allow the operations you will call, then click Create and copy the token from the key list. Task lookup does not grant permission to submit a generation. Confirm the application's balance can cover your first request; any trial allowance is whatever your account currently displays.
  5. Copy only the token value, without quotation marks, spaces, or 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.

[Copy an application API key or open Manage Keys]

[Create a separately named key with optional restrictions]

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:

bash
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:

json
{  "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:

json
{  "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:

json
{  "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:

bash
python -m pip install mcp-flux-proexport 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:

json
{  "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

  1. https://flux.mcp.acedata.cloud/health returning {"status":"ok"} checks endpoint reachability only.
  2. Confirm that the MCP client loads tools. flux_list_models is a reference tool; it does not verify downstream API access or balance.
  3. 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

ToolDescription
flux_generate_imageGenerate images from text prompts with model selection
flux_edit_imageEdit existing images with text instructions
flux_get_taskQuery status of a single generation task
flux_get_tasks_batchQuery multiple task statuses at once
flux_list_modelsList all available Flux models and capabilities
flux_list_actionsShow all tools and workflow examples

Available Prompts

PromptDescription
flux_image_generation_guideGuide for choosing the right tool and model
flux_prompt_writing_guideBest practices for writing effective prompts
flux_workflow_examplesCommon workflow patterns and examples

Supported Models

ModelQualitySpeedSize FormatBest For
flux-devGoodFastPixels (256-1440px)Quick prototyping
flux-proHighMediumPixels (256-1440px)Production use
flux-kontext-proHighMediumAspect ratiosImage editing
flux-kontext-maxHighestSlowerAspect ratiosComplex editing
flux-2-flexHighFastAspect ratiosFlux 2 balanced quality
flux-2-proHigherMediumAspect ratiosFlux 2 production
flux-2-maxHighestSlowerAspect ratiosFlux 2 maximum quality
flux-2-kleinGoodFastAspect ratiosFlux 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

VariableRequiredDefaultDescription
ACEDATACLOUD_API_TOKENYes (stdio)—API token from AceDataCloud
ACEDATACLOUD_API_BASE_URLNohttps://api.acedata.cloudAPI base URL
ACEDATACLOUD_OAUTH_CLIENT_IDNo—OAuth client ID (hosted mode)
ACEDATACLOUD_PLATFORM_BASE_URLNohttps://platform.acedata.cloudPlatform base URL
FLUX_REQUEST_TIMEOUTNo1800Request timeout in seconds
MCP_SERVER_NAMENofluxMCP server name
LOG_LEVELNoINFOLogging level

Development

Setup

bash
git clone https://github.com/AceDataCloud/FluxMCP.gitcd FluxMCPpip install -e ".[all]"cp .env.example .env# Edit .env with your API token

Lint & Format

bash
ruff check .ruff format .mypy core tools main.py

Test

bash
# Unit testspytest --cov=core --cov=tools
# Skip integration testspytest -m "not integration"
# With coverage reportpytest --cov=core --cov=tools --cov-report=html

Git Hooks

bash
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

Documentation

License

MIT License — see LICENSE for details.

Links

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.

Image model constraints

Use aspect ratios such as 1:1 or 16:9 for flux-2-flex, flux-2-pro, flux-2-max, and the Kontext models; pixel dimensions such as 1024x1024 are rejected for these models. flux-2-klein supports image generation only and is not an edit model.

Source: README.md at commit 5786d00

Tools

0
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Version history

16
  1. v2026.11.7.0LatestNov 7, 2026
  2. v2026.11.1.1Nov 1, 2026
  3. v2026.10.18.3Oct 18, 2026
  4. v2026.10.18.0Oct 18, 2026
  5. v2026.10.12.1Oct 12, 2026
  6. v2026.10.8.0Oct 8, 2026
  7. v2026.10.7.1Oct 7, 2026
  8. v2026.10.6.0Oct 6, 2026
  9. v2026.10.5.0Oct 5, 2026
  10. v2026.10.4.1Oct 4, 2026
  11. v2026.10.4.0Oct 4, 2026
  12. v2026.10.2.0Oct 2, 2026
  13. v2026.10.1.0Oct 1, 2026
  14. v2026.9.30.0Sep 30, 2026
  15. v2026.9.29.0Sep 29, 2026
  16. v2026.8.28.0Sep 16, 2026

Score

85% of the applicable checks met

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