mcp-midjourney 2026.3.20.2

MCP Server for Midjourney AI Image Generation via AceDataCloud API

MCP Midjourney

A Model Context Protocol (MCP) server for AI image and video generation using Midjourney through the AceDataCloud API.

Generate AI images, videos, and manage creative projects directly from Claude, VS Code, or any MCP-compatible client.

Features

• Image Generation - Create AI-generated images from text prompts
• Image Transformation - Upscale, create variations, zoom, and pan images
• Image Blending - Combine multiple images into creative fusions
• Reference-Based Generation - Use existing images as inspiration
• Image Description - Get AI descriptions of images (reverse prompt)
• Image Editing - Edit images with text prompts and masks
• Video Generation - Create videos from text and reference images
• Video Extension - Extend existing videos to make them longer
• Translation - Translate Chinese prompts to English
• Task Tracking - Monitor generation progress and retrieve results

Quick Start

1. Get Your API Token

1. Sign up at AceDataCloud Platform
2. Go to the API documentation page
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://midjourney.mcp.acedata.cloud/mcp

All requests require a Bearer token. Use the API token from Step 1.

Claude Desktop

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

{
  "mcpServers": {
    "midjourney": {
      "type": "streamable-http",
      "url": "https://midjourney.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": {
    "midjourney": {
      "type": "streamable-http",
      "url": "https://midjourney.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

VS Code (Copilot)

Add to your VS Code MCP config (.vscode/mcp.json):

{
  "servers": {
    "midjourney": {
      "type": "streamable-http",
      "url": "https://midjourney.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

Or install the Ace Data Cloud MCP extension for VS Code, which bundles all 11 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:

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

cURL Test

# Health check (no auth required)
curl https://midjourney.mcp.acedata.cloud/health

# MCP initialize
curl -X POST https://midjourney.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-midjourney
# or
uvx mcp-midjourney

# Set your API token
export ACEDATACLOUD_API_TOKEN="your_token_here"

# Run (stdio mode for Claude Desktop / local clients)
mcp-midjourney

# Run (HTTP mode for remote access)
mcp-midjourney --transport http --port 8000

Claude Desktop (Local)

{
  "mcpServers": {
    "midjourney": {
      "command": "uvx",
      "args": ["mcp-midjourney"],
      "env": {
        "ACEDATACLOUD_API_TOKEN": "your_token_here"
      }
    }
  }
}

Docker (Self-Hosting)

docker pull ghcr.io/acedatacloud/mcp-midjourney:latest
docker run -p 8000:8000 ghcr.io/acedatacloud/mcp-midjourney:latest

Clients connect with their own Bearer token — the server extracts the token from each request's Authorization header.

Available Tools

Image Generation

Tool	Description
midjourney_imagine	Generate images from a text prompt (creates 2x2 grid)
midjourney_transform	Transform images (upscale, variation, zoom, pan)
midjourney_blend	Blend multiple images together
midjourney_with_reference	Generate using a reference image as inspiration

Image Editing

Tool	Description
midjourney_edit	Edit an existing image with text prompt
midjourney_describe	Get AI descriptions of an image (reverse prompt)

Video

Tool	Description
midjourney_generate_video	Generate video from text and reference image
midjourney_extend_video	Extend existing video to make it longer

Utility

Tool	Description
midjourney_translate	Translate Chinese text to English for prompts
midjourney_get_seed	Get the seed value of a generated image

Tasks

Tool	Description
midjourney_get_task	Query a single task status
midjourney_get_tasks_batch	Query multiple tasks at once

Information

Tool	Description
midjourney_list_actions	List available API actions
midjourney_get_prompt_guide	Get prompt writing guide
midjourney_list_transform_actions	List transformation actions

Usage Examples

Generate Image from Prompt

User: Create a cyberpunk city at night

Claude: I'll generate a cyberpunk city image for you.
[Calls midjourney_imagine with prompt="Cyberpunk city at night, neon lights, rain, futuristic, detailed --ar 16:9"]

Upscale an Image

User: Upscale the second image

Claude: I'll upscale the top-right image from the grid.
[Calls midjourney_transform with image_id and action="upscale2"]

Blend Multiple Images

User: Blend these two images: [url1] and [url2]

Claude: I'll blend these images together.
[Calls midjourney_blend with image_urls=[url1, url2]]

Generate Video

User: Animate this image [url] with gentle movement

Claude: I'll create a video from this image.
[Calls midjourney_generate_video with image_url and prompt="Gentle camera movement, cinematic"]

Generation Modes

Mode	Description
fast	Recommended for most use cases (default)
turbo	Faster generation, uses more credits
relax	Slower generation, cheaper

Configuration

Environment Variables

Variable	Description	Default
ACEDATACLOUD_API_TOKEN	API token from AceDataCloud	Required
ACEDATACLOUD_API_BASE_URL	API base URL	https://api.acedata.cloud
MIDJOURNEY_DEFAULT_MODE	Default generation mode	fast
MIDJOURNEY_REQUEST_TIMEOUT	Request timeout in seconds	1800
LOG_LEVEL	Logging level	INFO

Command Line Options

mcp-midjourney --help

Options:
  --version          Show version
  --transport        Transport mode: stdio (default) or http
  --port             Port for HTTP transport (default: 8000)

Development

Setup Development Environment

# Clone repository
git clone https://github.com/AceDataCloud/mcp-midjourney.git
cd mcp-midjourney

# Create virtual environment
python -m venv .venv
source .venv/bin/activate  # or `.venv\Scripts\activate` on Windows

# Install with dev dependencies
pip install -e ".[dev,test]"

Run Tests

# Run unit tests
pytest

# Run with coverage
pytest --cov=core --cov=tools

# Run integration tests (requires API token)
pytest tests/test_integration.py -m integration

Code Quality

# Format code
ruff format .

# Lint code
ruff check .

# Type check
mypy core tools

Build & Publish

# Install build dependencies
pip install -e ".[release]"

# Build package
python -m build

# Upload to PyPI
twine upload dist/*

Project Structure

MCPMidjourney/
├── core/                   # Core modules
│   ├── __init__.py
│   ├── client.py          # HTTP client for Midjourney API
│   ├── config.py          # Configuration management
│   ├── exceptions.py      # Custom exceptions
│   ├── server.py          # MCP server initialization
│   ├── types.py           # Type definitions
│   └── utils.py           # Utility functions
├── tools/                  # MCP tool definitions
│   ├── __init__.py
│   ├── describe_tools.py  # Image description tools
│   ├── edits_tools.py     # Image editing tools
│   ├── imagine_tools.py   # Image generation tools
│   ├── info_tools.py      # Information tools
│   ├── task_tools.py      # Task query tools
│   ├── translate_tools.py # Translation tools
│   └── video_tools.py     # Video generation tools
├── prompts/                # MCP prompt templates
│   └── __init__.py
├── tests/                  # Test suite
├── deploy/                 # Deployment configs
│   └── production/
│       ├── deployment.yaml
│       ├── ingress.yaml
│       └── service.yaml
├── .env.example           # Environment template
├── .gitignore
├── CHANGELOG.md
├── Dockerfile             # Docker image for HTTP mode
├── docker-compose.yaml    # Docker Compose config
├── LICENSE
├── main.py                # Entry point
├── pyproject.toml         # Project configuration
└── README.md

API Reference

This server wraps the AceDataCloud Midjourney API:

• Midjourney Imagine API - Image generation
• Midjourney Describe API - Image description
• Midjourney Tasks API - Task queries
• Midjourney Edits API - Image editing
• Midjourney Videos API - Video generation
• Midjourney Translate API - Translation

Contributing

Contributions are welcome! Please:

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing)
5. Open a Pull Request

License

MIT License - see LICENSE for details.

Links

• AceDataCloud Platform
• Midjourney Official
• Model Context Protocol
• MCP Python SDK

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Made with love by AceDataCloud