Magic Hour

Lip Sync

lip_sync_create_video

What this API does

Create the same Lip Sync 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 lip sync into apps, pipelines, or tools

How it works (3 steps)

Upload your inputs (video, image, or audio) with Generate Upload URLs and copy the file_path.
Send a request to create a lip sync job with the basic fields.
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.

Use only with the user's own likeness or content they are authorized to use. Do not use for impersonation, deception, sexual content, or content involving minors.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`name`	No	Give your video a custom name for easy identification.	Lip Sync - dateTime
`style`	No	Attributes used to dictate the style of the output
`assets`	Yes	Provide the assets for lip-sync. For video, The `video_source` field determines whether `video_file_path` or `youtube_url` field is used
`end_seconds`	Yes	End time of your clip (seconds). Must be greater than start_seconds.
`max_fps_limit`	No	Defines the maximum FPS (frames per second) for the output video. If the input video's FPS is lower than this limit, the output video will retain the input FPS. This is useful for reducing unnecessary frame usage in scenarios where high FPS is not required.
`start_seconds`	Yes	Start time of your clip (seconds). Must be ≥ 0.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`id`	Yes	Unique 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_charged`	Yes	The 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.

Changed2 schema fields changedSep 24, 2026

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"
-}

changedInput schema / properties / style / properties / generation_mode / description

Previous value: -"A specific version of our lip sync system, optimized for different needs.\n* `lite` -  Fast and affordable lip sync - best for simple videos. Costs 1 credit per frame of video.\n* `standard` -  Natural, accurate lip sync - best for most creators. Costs 1 credit per frame of video.\n* `pro` -  Premium fidelity with enhanced detail - best for professionals. Costs 2 credits per frame of video.\n\nNote: `standard` and `pro` are only available for users on Creator, Pro, and Business tiers.\n              "New value: +"A specific version of our lip sync system, optimized for different needs.\n* `lite` -  Fast lip sync - best for simple videos. Costs 1 credit per frame of video.\n* `standard` -  Natural, accurate lip sync - best for most creators. Costs 1 credit per frame of video.\n* `pro` -  Premium fidelity with enhanced detail - best for professionals. Costs 2 credits per frame of video.\n\nNote: `standard` and `pro` are only available for users on Creator, Pro, and Business tiers.\n              "

Changed1 schema field changedSep 11, 2026

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"
+}

First observedSep 1, 2026

TDQS

A4.3/5.0

Behavior5/5

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

Annotations only declare readOnly=false, destructive=false, openWorld=true; the description goes far beyond by disclosing that this is an async job returning `id` plus `credits_charged` immediately, that credits are charged per rendered frame, that completion yields `downloads` URLs, and that the wait helper also returns `exact_download_urls`. It also adds file_path sourcing caveats (hotlinked URLs can fail) and an authorization/usage policy.

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

Conciseness4/5

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

Well front-loaded with headers and a numbered 3-step flow, and the MCP guidance is placed last where an agent needs it. It is longer than necessary, with the 'What this API does' and 'Good for' sections partly restating each other, but no sentence is actively harmful.

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 nested-schema, async, credit-metered generation tool, the description covers the full lifecycle: prepare inputs, submit, poll/wait, download. Output schema exists so return values need not be detailed, yet the description still clarifies the immediate response and the credit/estimate behavior.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3; the description adds real value on top by explaining file_path sourcing for `*_file_path` fields, the presigned-upload flow, the free-tier 576px resolution cap versus paid HD, and the role of start/end seconds. Mentioning a `face_swap_mode` field that is not in this schema is mildly noisy but not misleading.

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 and resource: programmatically create the same Lip Sync available in the browser, with concrete inputs (video, image, or audio) implied. However, it never distinguishes itself from the closest sibling, ai_talking_photo_create_talking_photo, which also animates a face to audio — an agent could plausibly confuse the two.

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 clear context for use ('Automation and batch processing', 'Adding lip sync into apps, pipelines, or tools') and the MCP guidance explicitly routes the agent to wait_for_video_project or the GET /v1/video-projects/{id} poll for the finished result. No explicit when-not-to-use or sibling-alternative comparison is offered.

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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