Seedance 2 Image to Video API: AI Image-to-Video

Seedance 2 Image to Video API Reference

Endpoint

POST https://api.muapi.ai/api/v1/seedance-2-image-to-video

Submit a job with your MuApi API key in the x-api-key header, then poll https://api.muapi.ai/api/v1/predictions/{request_id}/result until status is completed.

Parameters

Name	Type	Required	Description
prompt	string	Yes	Text description guiding the video animation. Use @character:<id> to reference a completed Seedance 2 Character generation.
images_list	array	Yes	1 image uses it as the start frame (first_last_frames mode). 2–9 images switches to omni_reference mode — reference them in your prompt with @image1, @image2, etc.
aspect_ratio	string	No	Output video aspect ratio.Options: 21:9, 16:9, 4:3, 1:1, 3:4, 9:16Default: "16:9"
duration	int	No	Video duration in seconds.Default: 5

cURL example

REQUEST_ID=$(curl -s -X POST https://api.muapi.ai/api/v1/seedance-2-image-to-video \
  -H "x-api-key: $MUAPI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"prompt":"<prompt>","images_list":[]}' | jq -r .request_id)

curl -s https://api.muapi.ai/api/v1/predictions/$REQUEST_ID/result -H "x-api-key: $MUAPI_API_KEY"

Python example

import os, time, requests

API = "https://api.muapi.ai/api/v1"
headers = {"x-api-key": os.environ["MUAPI_API_KEY"]}

r = requests.post(f"{API}/seedance-2-image-to-video", headers=headers, json={"prompt":"<prompt>","images_list":[]})
request_id = r.json()["request_id"]

while True:
    res = requests.get(f"{API}/predictions/{request_id}/result", headers=headers).json()
    if res["status"] == "completed":
        print(res["outputs"]); break
    if res["status"] == "failed":
        raise RuntimeError(res.get("error"))
    time.sleep(3)

Full docs and agent/MCP integration: llms.txt. Get an API key at muapi.ai/access-keys.