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MCP Midjourney

PyPI version PyPI downloads Python 3.10+ License: MIT MCP

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

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.ai

Connect directly on Claude.ai with OAuth — no API token needed:

  1. Go to Claude.ai Settings → Integrations → Add More

  2. Enter the server URL: https://midjourney.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):

{
  "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 AddHTTP

  3. Paste:

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

Claude Code

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"
      }
    }
  }
}

Cline

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"
      }
    }
  }
}

Amazon Q Developer

Add to your MCP configuration:

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

Roo Code

Add to Roo Code MCP settings:

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

Continue.dev

Add to .continue/config.yaml:

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

Zed

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"
        }
      }
    }
  }
}

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

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:

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.


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