Midjourney Image

Generate, edit, blend, upscale, and describe images with Midjourney via AceDataCloud API. Use when creating AI images from text prompts, editing existing images, generating 2x2 grids, upscaling, creating variations, blending multiple images, reverse-prompting from images, or generating video from images. Supports versions 5.2 through 8.

Midjourney Image Generation

Generate and manipulate AI images through AceDataCloud's Midjourney API.

Authentication

export ACEDATACLOUD_API_TOKEN="your-token-here"

Quick Start — Generate an Image

curl -X POST https://api.acedata.cloud/midjourney/imagine \
  -H "Authorization: Bearer $ACEDATACLOUD_API_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"prompt": "a futuristic city at sunset, cyberpunk style --ar 16:9", "wait": true}'

Generation Modes

Mode	Speed	Cost	Best For
fast	Fast	Standard	Most tasks (default)
relax	Slow	Cheaper	Batch generation
turbo	Fastest	Premium	Time-sensitive work

Midjourney Versions

Version	Notes
8	Latest, best quality
7	Great quality, fast
6.1	Stable, well-tested
6	Previous generation
5.2	Legacy

Core Workflows

1. Generate Images (Imagine)

Creates a 2x2 grid of 4 image variations.

POST /midjourney/imagine
{
  "prompt": "a serene mountain lake at dawn, photorealistic --ar 16:9 --v 7",
  "mode": "fast",
  "translation": true,
  "split_images": true
}

Set translation: true to auto-translate non-English prompts. Set split_images: true to get individual images besides the grid.

2. Upscale / Vary / Pan / Zoom

After generating a grid, use transform actions on individual images:

POST /midjourney/imagine
{
  "action": "upscale1",
  "image_id": "grid-image-id"
}

Available actions:

• upscale1–upscale4: Upscale individual quadrant
• variation1–variation4: Create variation of a quadrant
• variation_subtle / variation_strong: Subtle/strong variation of full image
• reroll: Re-generate with same prompt
• zoom_out_2x / zoom_out_1_5x: Zoom out
• pan_left / pan_right / pan_up / pan_down: Extend canvas

3. Edit an Image

Modify an existing image using a text prompt, optionally with a mask.

POST /midjourney/edits
{
  "image_url": "https://example.com/photo.jpg",
  "prompt": "add a rainbow in the sky",
  "mode": "fast"
}

4. Blend Images

Combine 2–5 images into a new composition.

POST /midjourney/imagine
{
  "action": "blend",
  "image_urls": [
    "https://example.com/image1.jpg",
    "https://example.com/image2.jpg"
  ]
}

5. Describe an Image (Reverse Prompt)

Get AI-generated text descriptions of an image (returns 4 options).

POST /midjourney/describe
{"image_url": "https://example.com/photo.jpg"}

6. Generate Video from Image

Create a video with a reference image and text prompt.

POST /midjourney/videos
{
  "image_url": "https://example.com/photo.jpg",
  "prompt": "the city comes alive with moving traffic",
  "resolution": "720p"
}

Prompt Parameters

Append these to your prompt text:

Parameter	Example	Description
--ar	--ar 16:9	Aspect ratio
--v	--v 7	Midjourney version
--q	--q 2	Quality (0.25, 0.5, 1, 2)
--s	--s 750	Stylization (0–1000)
--c	--c 50	Chaos/variety (0–100)
--no	--no text, watermark	Negative prompt
--seed	--seed 12345	Reproducible generation

Task Polling

POST /midjourney/tasks
{"task_id": "your-task-id"}

MCP Server

pip install mcp-midjourney

Or hosted: https://midjourney.mcp.acedata.cloud/mcp

Key tools: midjourney_imagine, midjourney_transform, midjourney_edit, midjourney_blend, midjourney_describe, midjourney_generate_video

Gotchas

• Imagine returns a 2x2 grid — use upscale/variation actions to work with individual images
• Use split_images: true to also receive individual cropped images alongside the grid
• Prompt parameters (--ar, --v, etc.) go inside the prompt string, not as separate fields
• translation: true auto-translates Chinese/other languages to English before sending to Midjourney
• Video generation requires a reference image_url — it cannot generate from text alone
• Available transform actions depend on the image — check available_actions in the response
• Get the seed with POST /midjourney/seed using the image_id for reproducible results