Prompt to outline - VideoGen API

Generate a video outline from a prompt. This outline can then be provided to the POST /outline-to-video endpoint, ensuring the resulting video closely follows your outlined structure.

Request

Authorization

Provide your bearer token in the

Authorization

header when making requests to protected resources.

Example:

Authorization: Bearer ********************

Body Params application/json

prompt

string

required

AI prompt that controls the script generation.

targetScriptWordCount

integer

optional

Target word count for the generated script. Not exact, but VideoGen's AI will attempt to generate a script close to this word count.

outputLanguageCode

string

optional

Two letter language code. See https://detectlanguage.com/languages for a list of supported language codes.

websiteUrls

array[string]

optional

List of website URLs to be scanned by VideoGen's AI and included along with the AI prompt to generate the script.

Example

{
  "prompt": "What is MCP Protocol?",
  "websiteUrls": [
    "https://modelcontextprotocol.io/introduction",
    "https://www.anthropic.com/news/model-context-protocol"
  ],
  "targetScriptWordCount": 250
}

Request samples

Shell

JavaScript

Java

Swift

PHP

Python

HTTP

Objective-C

Ruby

OCaml

Dart

Responses

🟢200Successfully generated outline

application/json

Body

outline

object (Outline)

required

sections

array[object (Section) {6}]

required

Sections of the video.

useGetty

boolean

optional

Option to include Getty/iStock assets, if available.

Default:

false

useGenerativeImage

boolean

optional

Option to include generative images.

Default:

false

imageGenStyle

string

optional

Style used for the generative images.

Example:

superhero comic book

musicUrl

string

optional

URL of the background music.

musicVolume

number

optional

Volume level for the background music, ranging from 0 (silent) to 1 (loudest).

>= 0<= 1

Default:

0.15

captionDetails

object (Caption Details)

optional

Style of captions in the video.

Example

{
  "outline": {
    "sections": [
      {
        "text": "The Model Context Protocol (MCP) is revolutionizing how artificial intelligence interacts with various data sources, akin to how USB-C ports standardize connections for devices. In a world where AI models often find themselves isolated from the data they require to function optimally, MCP serves as a vital bridge. This open protocol allows applications to seamlessly provide context to large language models (LLMs), enabling them to access and utilize data from diverse sources—be it local files, databases, or remote services."
      },
      {
        "text": "At its essence, MCP operates on a client-server architecture. Host applications, such as development environments and AI tools, connect to lightweight MCP servers, which expose specific capabilities. This structure not only simplifies the integration process but also allows developers the flexibility to switch between different LLM providers without the hassle of creating custom connections for each data source. By offering a growing list of pre-built integrations and best practices for data security, MCP empowers developers to build sophisticated agents and workflows that enhance the utility of AI."
      },
      {
        "text": "The significance of MCP extends beyond mere functionality; it represents a shift towards more connected and context-aware AI systems. As organizations like Block and Apollo adopt MCP, they highlight its potential to transform how AI tools retrieve and process information. With its open-source foundation, MCP invites developers to contribute and collaborate, paving the way for future innovations in AI technology. By simplifying the connection between AI and real-world applications, MCP is not just a protocol; it is a catalyst for a new era of intelligent, data-driven solutions."
      }
    ]
  }
}

🟠400Failed to generate outline