FluxMCP

# FluxMCP

<!-- mcp-name: io.github.AceDataCloud/mcp-flux-pro -->

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[![MCP](https://img.shields.io/badge/MCP-Compatible-green.svg)](https://modelcontextprotocol.io)
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A [Model Context Protocol (MCP)](https://modelcontextprotocol.io/) server for AI image generation and editing using [Flux](https://platform.acedata.cloud) through the [AceDataCloud](https://platform.acedata.cloud) 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

1. Sign up at [AceDataCloud Platform](https://platform.acedata.cloud)
2. Go to the [API documentation page](https://platform.acedata.cloud)
3. Click **"Acquire"** to get your API token
4. 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](https://claude.ai) with OAuth — **no API token needed**:

1. Go to Claude.ai **Settings → Integrations → Add More**
2. Enter the server URL: `https://flux.mcp.acedata.cloud/mcp`
3. Complete the OAuth login flow
4. Start using the tools in your conversation

#### Claude Desktop

Add to your config (`~/Library/Application Support/Claude/claude_desktop_config.json` on macOS):

```json
{
  "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`):

```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`):

```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](https://marketplace.visualstudio.com/items?itemName=acedatacloud.acedatacloud-mcp) for VS Code, which registers the hosted MCP servers with one-click setup.

#### JetBrains IDEs

1. Go to **Settings → Tools → AI Assistant → Model Context Protocol (MCP)**
2. Click **Add** → **HTTP**
3. Paste:

```json
{
  "mcpServers": {
    "flux": {
      "url": "https://flux.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}
```


#### Claude Code

Claude Code supports MCP servers natively:

```bash
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`:

```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`):

```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:

```json
{
  "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:

```json
{
  "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`:

```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`):

```json
{
  "language_models": {
    "mcp_servers": {
      "flux": {
        "url": "https://flux.mcp.acedata.cloud/mcp",
        "headers": {
          "Authorization": "Bearer YOUR_API_TOKEN"
        }
      }
    }
  }
}
```

#### cURL Test

```bash
# 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:

```bash
# 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)

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

#### Docker (Self-Hosting)

```bash
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  |

## 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://...", model="flux-kontext-pro")
```

### Check Task Status

```
"What's the status of my generation?"
→ flux_get_task(tas