klingai-image-to-video

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Generate videos from static images using Kling AI. Use when animating images, creating motion from stills, or building image-based content. Trigger with phrases like 'klingai image to video', 'kling ai animate image', 'klingai img2vid', 'animate picture klingai'.

Install

mkdir -p .claude/skills/klingai-image-to-video && curl -L -o skill.zip "https://mcp.directory/api/skills/download/4833" && unzip -o skill.zip -d .claude/skills/klingai-image-to-video && rm skill.zip

Installs to .claude/skills/klingai-image-to-video

About this skill

Kling AI Image-to-Video

Overview

Animate static images using the /v1/videos/image2video endpoint. Supports motion prompts, camera control, dynamic masks (motion brush), static masks, and tail images for start-to-end transitions.

Endpoint: POST https://api.klingai.com/v1/videos/image2video

Request Parameters

ParameterTypeRequiredDescription
model_namestringYeskling-v1-5, kling-v2-1, kling-v2-master, etc.
imagestringYesURL of the source image (JPG, PNG, WebP)
promptstringNoMotion description for the animation
negative_promptstringNoWhat to exclude
durationstringYes"5" or "10" seconds
aspect_ratiostringNo"16:9" default
modestringNo"standard" or "professional"
cfg_scalefloatNoPrompt adherence (0.0-1.0)
image_tailstringNoEnd-frame image URL (mutually exclusive with masks/camera)
camera_controlobjectNoCamera movement (mutually exclusive with masks/image_tail)
static_maskstringNoMask image URL for fixed regions
dynamic_masksarrayNoMotion brush trajectories
callback_urlstringNoWebhook for completion

Basic Image-to-Video

import jwt, time, os, requests

BASE = "https://api.klingai.com/v1"

def get_headers():
    ak, sk = os.environ["KLING_ACCESS_KEY"], os.environ["KLING_SECRET_KEY"]
    token = jwt.encode(
        {"iss": ak, "exp": int(time.time()) + 1800, "nbf": int(time.time()) - 5},
        sk, algorithm="HS256", headers={"alg": "HS256", "typ": "JWT"}
    )
    return {"Authorization": f"Bearer {token}", "Content-Type": "application/json"}

# Animate a landscape photo
response = requests.post(f"{BASE}/videos/image2video", headers=get_headers(), json={
    "model_name": "kling-v2-1",
    "image": "https://example.com/landscape.jpg",
    "prompt": "Clouds slowly drifting across the sky, gentle wind rustling through trees",
    "negative_prompt": "static, frozen, blurry",
    "duration": "5",
    "mode": "standard",
})

task_id = response.json()["data"]["task_id"]

# Poll for result
while True:
    time.sleep(15)
    result = requests.get(
        f"{BASE}/videos/image2video/{task_id}", headers=get_headers()
    ).json()
    if result["data"]["task_status"] == "succeed":
        print(f"Video: {result['data']['task_result']['videos'][0]['url']}")
        break
    elif result["data"]["task_status"] == "failed":
        raise RuntimeError(result["data"]["task_status_msg"])

Start-to-End Transition (image_tail)

Use image_tail to specify both the first and last frame. Kling interpolates the motion between them.

response = requests.post(f"{BASE}/videos/image2video", headers=get_headers(), json={
    "model_name": "kling-v2-master",
    "image": "https://example.com/sunrise.jpg",        # first frame
    "image_tail": "https://example.com/sunset.jpg",    # last frame
    "prompt": "Time lapse of sun moving across the sky",
    "duration": "5",
    "mode": "professional",
})

Motion Brush (dynamic_masks)

Draw motion paths for specific elements in the image. Up to 6 motion paths per image in v2.6.

response = requests.post(f"{BASE}/videos/image2video", headers=get_headers(), json={
    "model_name": "kling-v2-6",
    "image": "https://example.com/person-standing.jpg",
    "prompt": "Person walking forward naturally",
    "duration": "5",
    "dynamic_masks": [
        {
            "mask": "https://example.com/person-mask.png",  # white = selected region
            "trajectories": [
                {"x": 0.5, "y": 0.7, "t": 0.0},   # start position (normalized 0-1)
                {"x": 0.5, "y": 0.5, "t": 0.5},   # midpoint
                {"x": 0.5, "y": 0.3, "t": 1.0},   # end position
            ]
        }
    ],
})

Static Mask (freeze regions)

Keep specific areas of the image static while animating the rest.

response = requests.post(f"{BASE}/videos/image2video", headers=get_headers(), json={
    "model_name": "kling-v2-master",
    "image": "https://example.com/scene.jpg",
    "prompt": "Water flowing in the river, birds flying",
    "duration": "5",
    "static_mask": "https://example.com/buildings-mask.png",  # white = frozen
})

Mutual Exclusivity Rules

These features cannot be combined in a single request:

Feature Set AFeature Set B
image_taildynamic_masks, static_mask, camera_control
dynamic_masks / static_maskimage_tail, camera_control
camera_controlimage_tail, dynamic_masks, static_mask

Image Requirements

ConstraintValue
FormatsJPG, PNG, WebP
Max size10 MB
Min resolution300x300 px
Max resolution4096x4096 px
Mask formatPNG with white (selected) / black (excluded)

Error Handling

ErrorCauseFix
400 invalid imageURL unreachable or wrong formatVerify image URL is publicly accessible
400 mutual exclusivityCombined incompatible featuresUse only one feature set per request
task_status: failedImage too complex or low qualityUse higher resolution, clearer source
Mask mismatchMask dimensions differ from sourceEnsure mask matches source image dimensions

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