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KlingMCP

by AceDataCloud
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Python
Hybrid

kling_generate_video_from_image

Generate AI video by animating a start image, end image, or both. Describe motion and transitions in a prompt. Supports various models, durations, and aspect ratios.

Instructions

Generate AI video using reference images as start and/or end frames.

This allows you to control the video by specifying what the first frame
and/or last frame should look like. Kling will generate smooth motion between them.

Use this when:
- You have a specific image you want to animate
- You want to create a video transition between two images
- You need precise control over the video's visual content

At least one of start_image_url or end_image_url must be provided.

Returns:
    Task ID and generated video information including URLs and state.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesDescription of the video motion and content. Describe what should happen in the video, how objects should move, what transitions to include.
start_image_urlNoURL of the image to use as the first frame of the video. The video will animate from this image.
end_image_urlNoURL of the image to use as the last frame of the video. The video will animate towards this image.
modelNoKling model to use. Default: 'kling-v2-master'.kling-v2-master
modeNoGeneration mode. 'std' (standard, default) or 'pro' (higher quality).std
aspect_ratioNoVideo aspect ratio. Usually should match your input image ratio.16:9
durationNoVideo duration in seconds. For kling-v3/kling-v3-omni: 3-15 (integer). Other models: 5 or 10.
generate_audioNoWhether to generate audio synchronously. Supported by kling-v3, kling-v3-omni, and kling-v2-6 (pro mode only).
negative_promptNoThings to avoid in the video.
cfg_scaleNoClassifier-free guidance scale. Higher values follow the prompt more strictly.
camera_controlNoCamera control as JSON string.
timeoutNoTimeout in seconds for the API to return data. Default is 300.
callback_urlNoWebhook callback URL for asynchronous notifications.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Tool Definition Quality

A3.8/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description must carry the full burden. It states 'generate AI video', implying creation, but fails to disclose behavioral traits like whether the operation is asynchronous, what side effects exist (e.g., file storage), permission requirements, or rate limits. This lack of detail compromises transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise, with a clear opening sentence, a short explanatory paragraph, bullet points for usage, and a structured return note. Every sentence serves a purpose, and the formatting aids readability.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (13 parameters, output schema) and the richness of the input schema, the description provides sufficient high-level context. It explains the core workflow and usage cases, though it could briefly mention model-specific constraints (e.g., duration limits) that are only in the schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the description adds limited value beyond the schema. It does note the constraint 'At least one of start_image_url or end_image_url must be provided', which is not enforced in the schema's required fields. This is a helpful addition, but otherwise the description does not enhance parameter understanding.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb 'generate' and identifies the resource 'AI video using reference images as start and/or end frames'. It clearly distinguishes from sibling tools like text-to-video generation (e.g., kling_generate_video) by emphasizing image-driven control.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit 'Use this when' bullet points that cover common scenarios (animating an image, transitions, precise control). However, it does not mention when not to use it or suggest alternatives, such as kling_generate_video for text-only prompts.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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