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MCP server for Midjourney AI image generation and editing
MCP server for Midjourney AI image generation and editing
Remote endpoints: streamable-http: https://midjourney.mcp.acedata.cloud/mcp
This is a well-structured MCP server for Midjourney API integration with proper authentication, reasonable code quality, and permissions appropriate to its purpose. However, there are several moderate-severity concerns: the OAuth provider uses in-memory token storage unsuitable for multi-replica deployments, extensive unvalidated debug logging that could expose sensitive JWT claims and API internals, missing input validation on key parameters, and broad exception handling that masks failures. These issues do not represent critical security vulnerabilities but warrant attention before production deployment at scale. Supply chain analysis found 5 known vulnerabilities in dependencies (0 critical, 3 high severity). Package verification found 1 issue (1 critical, 0 high severity).
5 files analyzed · 15 issues found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
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Set these up before or after installing:
Environment variable: ACEDATACLOUD_API_TOKEN
Available as Local & Remote
This plugin can run on your machine or connect to a hosted endpoint. during install.
From the project's GitHub README.
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.
| 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_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. |
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.
Connect directly on Claude.ai with OAuth — no API token needed:
https://midjourney.mcp.acedata.cloud/mcpAdd 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"
}
}
}
}
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"
}
}
}
}
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 15 MCP servers with one-click setup.
{
"mcpServers": {
"midjourney": {
"url": "https://midjourney.mcp.acedata.cloud/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_TOKEN"
}
}
}
}
Claude Code supports MCP servers natively:
claude mcp add midjourney --transport http https://midjourney.mcp.acedata.cloud/mcp \
-h "Authorization: Bearer YOUR_API_TOKEN"
Or add to your project's .mcp.json:
{
"mcpServers": {
"midjourney": {
"type": "streamable-http",
"url": "https://midjourney.mcp.acedata.cloud/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_TOKEN"
}
}
}
}
Add to Cline's MCP settings (.cline/mcp_settings.json):
{
"mcpServers": {
"midjourney": {
"type": "streamable-http",
"url": "https://midjourney.mcp.acedata.cloud/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_TOKEN"
}
}
}
}
Add to your MCP configuration:
{
"mcpServers": {
"midjourney": {
"type": "streamable-http",
"url": "https://midjourney.mcp.acedata.cloud/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_TOKEN"
}
}
}
}
Add to Roo Code MCP settings:
{
"mcpServers": {
"midjourney": {
"type": "streamable-http",
"url": "https://midjourney.mcp.acedata.cloud/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_TOKEN"
}
}
}
}
Add to .continue/config.yaml:
mcpServers:
- name: midjourney
type: streamable-http
url: https://midjourney.mcp.acedata.cloud/mcp
headers:
Authorization: "Bearer YOUR_API_TOKEN"
Add to Zed's settings (~/.config/zed/settings.json):
{
"language_models": {
"mcp_servers": {
"midjourney": {
"url": "https://midjourney.mcp.acedata.cloud/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_TOKEN"
}
}
}
}
}
# 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"}}}'
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
{
"mcpServers": {
"midjourney": {
"command": "uvx",
"args": ["mcp-midjourney"],
"env": {
"ACEDATACLOUD_API_TOKEN": "your_token_here"
}
}
}
}
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.
| 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 |
| Tool | Description |
|---|---|
midjourney_edit | Edit an existing image with text prompt |
midjourney_describe | Get AI descriptions of an image (reverse prompt) |
| Tool | Description |
|---|---|
midjourney_generate_video | Generate video from text and reference image |
midjourney_extend_video | Extend existing video to make it longer |
| Tool | Description |
|---|---|
midjourney_translate | Translate Chinese text to English for prompts |
midjourney_get_seed | Get the seed value of a generated image |
| Tool | Description |
|---|---|
midjourney_get_task | Query a single task status |
midjourney_get_tasks_batch | Query multiple tasks at once |
| Tool | Description |
|---|---|
midjourney_list_actions | List available API actions |
midjourney_get_prompt_guide | Get prompt writing guide |
midjourney_list_transform_actions | List transformation actions |
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"]
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"]
User: Blend these two images: [url1] and [url2]
Claude: I'll blend these images together.
[Calls midjourney_blend with image_urls=[url1, url2]]
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"]
| Mode | Description |
|---|---|
fast | Recommended for most use cases (default) |
turbo | Faster generation, uses more credits |
relax | Slower generation, cheaper |
| 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 |
mcp-midjourney --help
Options:
--version Show version
--transport Transport mode: stdio (default) or http
--port Port for HTTP transport (default: 8000)
# 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 unit tests
pytest
# Run with coverage
pytest --cov=core --cov=tools
# Run integration tests (requires API token)
pytest tests/test_integration.py -m integration
# Format code
ruff format .
# Lint code
ruff check .
# Type check
mypy core tools
# Install build dependencies
pip install -e ".[release]"
# Build package
python -m build
# Upload to PyPI
twine upload dist/*
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
This server wraps the AceDataCloud Midjourney API:
Contributions are welcome! Please:
git checkout -b feature/amazing)git commit -m 'Add amazing feature')git push origin feature/amazing)MIT License - see LICENSE for details.
Made with love by AceDataCloud
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