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Audio-to-Video

audio_to_video_create_video

What this API does

Create the same Audio To Video you can make in the browser, but programmatically, so you can automate it, run it at scale, or connect it to your own app or workflow.

Good for

  • Automation and batch processing

  • Adding audio to video into apps, pipelines, or tools

How it works (3 steps)

  1. Upload your inputs (video, image, or audio) with Generate Upload URLs and copy the file_path.

  2. Send a request to create a audio to video job with the basic fields.

  3. Check the job status until it's complete, then download the result from downloads.

Key options

  • Inputs: usually a file, sometimes a YouTube link, depending on project type

  • Resolution: free users are limited to 576px; higher plans unlock HD and larger sizes

  • Extra fields: e.g. face_swap_mode, start_seconds/end_seconds, or a text prompt

Cost
Credits are only charged for the frames that actually render. You'll see an estimate when the job is queued, and the final total after it's done.

For detailed examples, see the product page.

MCP guidance:

  • This starts an async video generation job and returns id plus credits_charged immediately. If the user wants the finished result, call the wait_for_video_project helper with the returned id, or poll the matching GET /v1/video-projects/{id} endpoint until status is complete, error, or canceled. Completed projects include downloads with direct URLs. The custom wait helper also returns exact_download_urls separately from expiration metadata.

  • For *_file_path values, prefer an existing Magic Hour file path or a file_path returned by the upload-URL endpoint after the file bytes are uploaded. Direct public media URLs may work when they are stable, fetchable, and return raw file bytes, but hotlinked URLs can fail; when in doubt, use the presigned upload flow first and pass the returned file_path.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoGive your video a custom name for easy identification.Audio To Video - dateTime
styleNoAttributes used to dictate the style of the output
assetsYesProvide the audio file and an optional reference image.
resolutionNoOutput video resolution. Defaults to `720p` on paid tiers and `480p` on free tiers.
end_secondsYesEnd time of your clip (seconds). Must be greater than start_seconds.
start_secondsNoStart time of your clip (seconds). Must be ≥ 0.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesUnique ID of the video. Use it with the [Get video Project API](https://docs.magichour.ai/api-reference/video-projects/get-video-details) to fetch status and downloads.
credits_chargedYesThe amount of credits deducted from your account to generate the video. If the status is not 'complete', this value is an estimate and may be adjusted upon completion based on the actual FPS of the output video. If video generation fails, credits will be refunded, and this field will be updated to include the refund.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • removedInput schema / properties / context
      Removed value: -{
      -  "description": "Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as \"a user\", \"the customer\", or \"an account\". Example: \"Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution.\"",
      -  "type": "string"
      -}
  2. Changed1 schema field changed
    • addedInput schema / properties / context
      Added value: +{
      +  "description": "Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as \"a user\", \"the customer\", or \"an account\". Example: \"Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution.\"",
      +  "type": "string"
      +}
  3. First observed

TDQS

A4.1/5.0
Behavior5/5

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

Annotations only cover readOnly/destructive/openWorld; the description adds substantial context beyond them — that it is an async job returning id plus credits_charged immediately, the complete/error/canceled terminal states, that credits are charged only for rendered frames with an estimate then final total, and that hotlinked URLs may fail so the presigned upload flow should be preferred.

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

Conciseness3/5

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

Front-loaded and organized under clear headers, but considerably longer than needed for invocation and padded with template text (product page link, 'Key options' list of fields that don't exist on this tool). Several sentences do not earn their place.

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

Completeness5/5

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

For a complex async generation tool with nested params and an existing output schema, the description supplies everything an agent needs: the async lifecycle, the wait helper, download locations, cost behavior, and file-path sourcing — no critical gap remains.

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%, so the baseline is 3; the schema already documents every field including the nested assets. The description adds useful file_path handling guidance but also references fields not present here (e.g. face_swap_mode) and a '576px' free-tier limit that conflicts with the schema's 480p/720p/1080p enum.

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

Purpose4/5

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

States a specific verb+resource ('Create ... Audio To Video ... programmatically') and lists intended uses like adding audio to video. However, it never distinguishes this tool from the many create_video siblings (image_to_video, text_to_video, video_to_video), and the copy-pasted 'depending on project type' phrasing weakens specificity.

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?

Gives a clear 'Good for' context and a concrete 3-step workflow, and the MCP guidance explicitly tells the agent to use wait_for_video_project or poll GET /v1/video-projects/{id} for the finished result. It lacks an explicit statement of when to prefer this over the other *_create_video siblings.

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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