Midjourney CLI

A command-line tool for AI image and video generation using Midjourney through the AceDataCloud API.

Generate AI images, edit photos, create videos, and manage tasks directly from your terminal — no MCP client required.

Features

• Image Generation — Generate from prompts, transform (upscale/variation/zoom/pan), blend images
• Image Editing — Edit with prompts and masks, describe images (reverse prompt), translate prompts
• Video Generation — Generate video from text + reference image, extend existing videos
• Task Management — Query tasks, batch query, wait with polling
• Rich Output — Beautiful terminal tables and panels via Rich
• JSON Mode — Machine-readable output with --json for piping
• Multiple Modes — fast, turbo, relax generation modes
• V8 Support — HD mode, ultra quality, style references

Quick Start

1. Get API Token

Get your API token from AceDataCloud Platform:

1. Sign up or log in
2. Navigate to Midjourney API
3. Click "Acquire" to get your token

2. Install

# Install with pip
pip install midjourney-pro-cli

# Or with uv (recommended)
uv pip install midjourney-pro-cli

# Or from source
git clone https://github.com/AceDataCloud/MidjourneyCli.git
cd MidjourneyCli
pip install -e .

3. Configure

# Set your API token
export ACEDATACLOUD_API_TOKEN=your_token_here

# Or use .env file
cp .env.example .env
# Edit .env with your token

4. Use

# Generate an image
midjourney imagine "A majestic lion at sunset, cinematic lighting"

# Generate with V8 HD mode
midjourney imagine "Cyberpunk city" --version 8 --hd --mode turbo

# Upscale a specific image from the grid
midjourney transform <image_id> upscale1

# Edit an existing image
midjourney edit https://example.com/photo.jpg "Add a sunset background"

# Describe an image (reverse prompt)
midjourney describe https://example.com/photo.jpg

# Generate video
midjourney video "A cat walking" --image-url https://example.com/cat.jpg

# Check task status
midjourney task <task_id>

# Wait for completion
midjourney wait <task_id> --interval 5

Commands

Image Generation

Command	Description
midjourney imagine <prompt>	Generate a 2x2 grid of images from text
midjourney transform <image_id> <action>	Upscale, vary, zoom, or pan an image
midjourney blend <url1> <url2> [...]	Blend 2-5 images together

Image Editing

Command	Description
midjourney edit <image_url> <prompt>	Edit an image with a text prompt
midjourney describe <image_url>	Get 4 AI descriptions of an image
midjourney translate <content>	Translate Chinese text to English prompts

Video Generation

Command	Description
midjourney video <prompt> --image-url <url>	Generate video from text + image
midjourney extend-video <video_id> <prompt>	Extend an existing video

Task Management

Command	Description
midjourney task <task_id>	Query a single task status
midjourney tasks <id1> <id2> [...]	Query multiple tasks at once
midjourney wait <task_id>	Wait for task completion with polling
midjourney seed <image_id>	Get the seed value of a generated image

Utilities

Command	Description
midjourney modes	List available generation modes
midjourney versions	List available Midjourney versions
midjourney actions	List available transform actions
midjourney config	Show current configuration

Global Options

--token TEXT    API token (or set ACEDATACLOUD_API_TOKEN env var)
--version       Show version
--help          Show help message

Most commands support:

--json          Output raw JSON (for piping/scripting)
--mode TEXT     Generation mode: fast (default), turbo, relax

Transform Actions

After generating a 2x2 grid with imagine:

Action	Description
upscale1-4	Upscale one of the 4 grid images
upscale_2x / upscale_4x	Further upscale an upscaled image
variation1-4	Create variations of one grid image
variation_subtle / variation_strong	Create subtle/strong variations
variation_region	Edit specific region with mask
reroll	Regenerate all 4 images
zoom_out_2x / zoom_out_1_5x	Zoom out
pan_left/right/up/down	Expand image in a direction

Scripting & Piping

The --json flag outputs machine-readable JSON suitable for piping:

# Generate and extract task ID
TASK_ID=$(midjourney imagine "sunset" --json | jq -r '.task_id')

# Wait for completion and get image URL
midjourney wait $TASK_ID --json | jq -r '.image_url'

# Batch generate from a file of prompts
while IFS= read -r prompt; do
  midjourney imagine "$prompt" --json >> results.jsonl
done < prompts.txt

Available Versions

Version	Notes
5.2	Stable, well-tested
6	Improved prompt understanding
6.1	Enhanced detail and coherence
7	Better composition and realism
8	Latest V8 Alpha — HD and ultra quality support

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_REQUEST_TIMEOUT	Timeout in seconds	1800

Development

Setup Development Environment

# Clone repository
git clone https://github.com/AceDataCloud/MidjourneyCli.git
cd MidjourneyCli

# 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=midjourney_cli

# 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 midjourney_cli

Build & Publish

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

# Build package
python -m build

# Upload to PyPI
twine upload dist/*

Docker

# Pull the image
docker pull ghcr.io/acedatacloud/midjourney-cli:latest

# Run a command
docker run --rm -e ACEDATACLOUD_API_TOKEN=your_token \
  ghcr.io/acedatacloud/midjourney-cli imagine "A happy scene"

# Or use docker-compose
docker compose run --rm midjourney-cli imagine "A happy scene"

Project Structure

MidjourneyCli/
├── midjourney_cli/         # Main package
│   ├── __init__.py
│   ├── __main__.py        # python -m midjourney_cli entry point
│   ├── main.py            # CLI entry point
│   ├── core/              # Core modules
│   │   ├── client.py      # HTTP client for Midjourney API
│   │   ├── config.py      # Configuration management
│   │   ├── exceptions.py  # Custom exceptions
│   │   └── output.py      # Rich terminal formatting
│   └── commands/          # CLI command groups
│       ├── imagine.py     # Image generation (imagine, transform, blend)
│       ├── edit.py        # Edit, describe, translate commands
│       ├── video.py       # Video generation commands
│       ├── task.py        # Task management commands
│       └── info.py        # Info & utility commands
├── tests/                  # Test suite
├── Dockerfile             # Container image
├── .env.example           # Environment template
├── pyproject.toml         # Project configuration
└── README.md

Midjourney CLI vs MCP Midjourney

Feature	Midjourney CLI	MCP Midjourney
Interface	Terminal commands	MCP protocol
Usage	Direct shell, scripts, CI/CD	Claude, VS Code, MCP clients
Output	Rich tables / JSON	Structured MCP responses
Automation	Shell scripts, piping	AI agent workflows
Install	pip install midjourney-pro-cli	pip install mcp-midjourney

Both tools use the same AceDataCloud API and share the same API token.

API Reference

This tool wraps the AceDataCloud Midjourney API:

• Midjourney Imagine API — Image generation
• Midjourney Edits API — Image editing
• Midjourney Videos API — Video generation

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
• MCP Midjourney — MCP server version
• Midjourney Official

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Made with ❤️ by AceDataCloud