Skip to main content
Glama

sora_generate_video_v2_async

Generate AI videos asynchronously; submit request with callback URL to receive result when generation completes.

Instructions

Generate an AI video asynchronously using Sora Version 2 with callback.

Similar to sora_generate_video_v2 but returns immediately with a task ID.
The result will be POSTed to your callback URL when generation completes.

Use this when:
- You don't want to wait for the generation to complete
- You have a webhook endpoint to receive results
- You're integrating with an async workflow

Returns:
    Task ID that you can use to correlate with the callback.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesDescription of the video to generate.
callback_urlYesURL to receive the callback when video generation is complete. The result will be POSTed to this URL as JSON.
modelNoSora model version.sora-2
durationNoVideo duration in seconds. Options: 4, 8, or 12.
sizeNoVideo resolution in pixels.1280x720
image_urlsNoOptional list of reference image URLs. Only the first image is used.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

No annotations are provided, so the description carries full burden. It discloses async behavior, callback mechanism, return of task ID, and that result is POSTed to callback URL. It does not cover error handling, rate limits, or callback failure scenarios, but the core behavioral traits are well covered.

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?

Extremely concise: three sentences for purpose, three bullet points for usage, and a clear return section. No filler language. Every sentence earns its place. Front-loaded with action and key differentiator.

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 is async with callback and has an output schema (though not shown), the description covers return values (task ID) and the callback process. It does not mention output schema details or error handling, but for an async tool the description is reasonably complete. Leaving a small gap for missing timeout or failure behavior, thus 4.

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 description coverage is 100% (all parameters have descriptions), baseline is 3. The description adds minor value by noting 'Only the first image is used' for image_urls, but otherwise does not significantly extend beyond schema descriptions. Hence a 3 is appropriate.

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 clearly states the tool generates an AI video asynchronously using Sora Version 2 with a callback. It distinguishes from its synchronous sibling sora_generate_video_v2 by highlighting the immediate return of a task ID. This meets the 'specific verb+resource' standard and differentiates from siblings.

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

Usage Guidelines5/5

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

Explicitly lists three use cases in bullet points: not waiting for completion, having a webhook endpoint, and integrating with async workflows. Also contrasts with the synchronous version, providing clear when-to-use guidance. No when-not-to-use conditions are mentioned, but the positive guidance is strong.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/AceDataCloud/SoraMCP'

If you have feedback or need assistance with the MCP directory API, please join our Discord server