MidjourneyMCP

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

Tool Reference

Tool	Description
`midjourney_imagine`	Generate AI images from a text prompt using Midjourney.
`midjourney_transform`	Transform an existing Midjourney image with various operations.
`midjourney_blend`	Blend multiple images together using Midjourney.
`midjourney_with_reference`	Generate images using a reference image as inspiration.
`midjourney_edit`	Edit an existing image using Midjourney.
`midjourney_describe`	Get AI-generated descriptions of an image.
`midjourney_generate_video`	Generate a video from text prompt and reference image using Midjourney.
`midjourney_extend_video`	Extend an existing Midjourney video to make it longer.
`midjourney_translate`	Translate Chinese text to English for use as Midjourney prompts.
`midjourney_shorten`	Analyze and shorten long Midjourney prompts while preserving key ideas.
`midjourney_get_seed`	Get the seed value of a previously generated Midjourney image.
`midjourney_get_task`	Query the status and result of a Midjourney generation task.
`midjourney_get_tasks_batch`	Query multiple Midjourney generation tasks at once.
`midjourney_list_actions`	List all available Midjourney API actions and corresponding tools.
`midjourney_get_prompt_guide`	Get guidance on writing effective prompts for Midjourney.
`midjourney_list_transform_actions`	List all available transformation actions for Midjourney images.

Connect: hosted OAuth, API token, or local stdio

The hosted endpoint is https://midjourney.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-midjourney` 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://midjourney.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 midjourney https://midjourney.mcp.acedata.cloud/mcp, then claude mcp login midjourney. Check /mcp. Claude Code MCP guide.
Cursor: Add a remote server with only https://midjourney.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://midjourney.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 midjourney --url https://midjourney.mcp.acedata.cloud/mcp, then codex mcp login midjourney. Its user settings are in ~/.codex/config.toml. Official Codex MCP guide.

Cursor project config (OAuth):

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

VS Code-specific workspace config (OAuth):

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

Hosted API token

Sign in at AceDataCloud Platform, open the service page, and obtain an API credential. A fixed Bearer header is useful when your client lacks OAuth; an invalid header does not fall back to OAuth in Claude Code. The header value is sensitive, so keep it out of committed files and screenshots.

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 midjourney https://midjourney.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": {
    "midjourney": {
      "type": "http",
      "url": "https://midjourney.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": {
    "midjourney": {
      "url": "https://midjourney.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-midjourney-token", "type": "promptString", "description": "AceDataCloud API token", "password": true}
  ],
  "servers": {
    "midjourney": {
      "type": "http",
      "url": "https://midjourney.mcp.acedata.cloud/mcp",
      "headers": {"Authorization": "Bearer ${input:acedata-midjourney-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:

python -m pip install mcp-midjourney
export ACEDATACLOUD_API_TOKEN='YOUR_API_TOKEN'
mcp-midjourney

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

Keep this user-level file private. Self-hosted HTTP uses mcp-midjourney --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

https://midjourney.mcp.acedata.cloud/health returning {"status":"ok"} checks endpoint reachability only.
Confirm that the MCP client loads tools. midjourney_list_actions is a reference tool; it does not verify downstream API access or balance.
If you need a full API check, call midjourney_generate_video with your own valid input after reviewing current service documentation and displayed pricing. If the result contains a task ID, call midjourney_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

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`
`ACEDATACLOUD_OAUTH_CLIENT_ID`	OAuth client ID (hosted mode)	—
`ACEDATACLOUD_PLATFORM_BASE_URL`	Platform base URL	`https://platform.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/MidjourneyMCP.git
cd MidjourneyMCP

# 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

MidjourneyMCP/
├── 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:

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

Service details

License

MIT License - see LICENSE for details.

Links

Made with love by AceDataCloud

Metadata

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