Magic Hour

One API key for many video/image models: Sora 2, Veo 3.1, Kling 3.0, Seedance, MiniMax H3, WAN 2.2, LTX 2.3 (video) and GPT-image, Nano Banana Pro, Seedream, Flux, Z-Image (image). Jobs are async; the scripts below submit, poll every ~5s, and print a single JSON line when done.

Fastest route: hosted MCP server (zero install)

Magic Hour runs a remote MCP server at https://mcp.magichour.ai/ (docs: https://magichour.ai/mcp). If your agent can attach MCP servers, add it with header Authorization: Bearer $MAGIC_HOUR_API_KEY (Claude web/desktop uses OAuth, client id magic-hour-mcp). It exposes image, video and audio generation tools plus upload (videoAssets_generatePresignedUrl) and wait/status tools, so no local SDK is needed. The scripts below are the fallback for agents without MCP, or when you want plain JSON from a shell.

Setup (script route)

1. Free key (400 credits on signup + 100/day, no card): https://magichour.ai/developer
2. export MAGIC_HOUR_API_KEY=mhk_...
3. pip install magic_hour (official SDK, Python >= 3.9)

Scripts

All scripts print one JSON object to stdout: {project_id, status, model, url, urls, credits_charged, ...} and exit non-zero with {"status":"error","error":{...}} on failure. Add --download-dir DIR to also save the file locally (downloaded_paths in the output). Add --no-wait to return immediately (status: "queued") and check later with status.py.

# Text -> video (default: wan-2.2, 5s, 480p, 16:9 = 120 credits, free tier)
python3 {baseDir}/scripts/text_to_video.py "a corgi surfing at golden hour, slow-motion, cinematic" \
  --model wan-2.2 --duration 5 --resolution 480p --aspect-ratio 16:9 --download-dir ./out

# Image -> video (local file is uploaded automatically; public https URL also works)
python3 {baseDir}/scripts/image_to_video.py ./photo.png "slow push-in, hair moves in the wind" \
  --model kling-3.0 --duration 5 --resolution 720p

# Text -> image(s)
python3 {baseDir}/scripts/generate_image.py "isometric cozy coffee shop, soft morning light" \
  --model nano-banana-pro --count 2 --aspect-ratio 1:1

# Poll a queued project
python3 {baseDir}/scripts/status.py <project_id> --kind video --wait

Choosing a video model

Model	Durations (s)	Credits/sec	Notes
wan-2.2	3-10, 15	24	FREE. Default. Cheap general-purpose clips.
ltx-2.3	1-10, 15, 20, 25, 30	24	FREE. Longest free clips (30s).
minimax-h3	1-10, 15, 20, 25, 30	24	FREE. Up to 1080p.
seedance-1.5	4-12	30	Good value step up.
kling-2.6	5, 10	36
kling-3.0	3-15	48	Best motion/physics for the price.
veo3.1-lite	4, 6, 8, 16...56	48
veo3.1 / veo3.1-audio	4, 6, 8, 16...56	96	Cinematic; -audio adds sound (--audio).
sora-2	4, 8, 12, 24, 36, 48, 60	120	Complex multi-shot scenes. 720p max.
seedance-2.0-mini / 2.0 / 2.5	4-15 / 4-15 / 4-30	96 / 120 / 120	720p max.

Rules of thumb:

• Cost = credits/sec x duration (e.g. kling-3.0 5s = 240). Failed jobs are auto-refunded. Tell the user the estimated cost before spending more than ~500 credits.
• Stay on wan-2.2 / ltx-2.3 / minimax-h3 unless the user asks for quality or has a paid plan; the free tier is ~100 credits/day.
• Duration must be in the model's allowed list or the API rejects the job. The scripts warn on stderr if it is not.
• Use 9:16 for shorts/reels, 16:9 for landscape, 1:1 for social tiles.
• Image-to-video: keep the prompt about motion ("camera slowly orbits", "she turns and smiles"); the image already defines the look.

Image models

default (good all-rounder), gpt-image-2 (text rendering, instructions), nano-banana-pro (photoreal, editing), seedream-5-pro, flux-2-klein (fast), z-image-turbo (fastest), qwen-edit (edits). Images are cheap (roughly 5-50 credits each depending on model).

Prompting tips

• Video prompts: subject + action + camera move + lighting/style + mood, 1-3 sentences. Avoid listing many scenes for short clips.
• Rendering takes ~1-5 minutes for video, seconds for images. Output URLs expire after a while; download with --download-dir if the user needs the file.
• If status is error, read error.message, fix the request (usually duration/resolution/model), and retry once.

References

• {baseDir}/references/api.md - raw HTTP endpoints, poll loop, file upload (use if the SDK is unavailable, e.g. with curl).
• {baseDir}/references/models.md - full model catalogue and pricing.
• Docs: https://docs.magichour.ai - Other integrations: PyPI langchain-magic-hour, llama-index-tools-magic-hour; npm langchain-magic-hour, magic-hour-ai-provider; hosted MCP https://mcp.magichour.ai/ (legacy self-hosted: github.com/magichourhq/magic-hour-mcp).