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.

Changed1 schema field changedOct 7, 2026

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 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. Requires visible mouth movement in the opening seconds of the input video. Costs 1 credit per frame of video.\n* `pro` -  Premium fidelity with enhanced detail - best for professionals. Requires visible mouth movement in the opening seconds of the input video. Costs 2 credits per frame of video.\n\nIf your source is a still image, including a still image saved as a static video, use [AI Talking Photo](https://docs.magichour.ai/api-reference/video-projects/ai-talking-photo) with the original image and your audio instead.\n\nNote: `pro` is only available for users on Creator, Pro, and Business tiers.\n              "

Changed1 schema field changedSep 24, 2026

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 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"
-}

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?

The description adds substantial context beyond the annotations: it discloses that the call is asynchronous and returns immediately with id and credits_charged, that credits are charged only for rendered frames with an estimate at queue time, the terminal statuses to poll for, that completed projects expose downloads with expiration metadata, and the input-file sourcing rules (prefer presigned upload file_path over hotlinked URLs). It also states authorization/content policy limits (own likeness only, no impersonation, deception, sexual content, or minors).

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?

Content is organized under clear headers, front-loaded with the purpose, and the MCP guidance is placed last where an agent can act on it. It is on the long side and carries some product-page boilerplate (cost paragraph, product/docs links) that is not strictly needed to invoke the tool correctly.

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, 6-parameter async generation tool with a full output schema and annotations, the description covers everything needed: initiation semantics, the upload prerequisite, the polling/wait path, credit implications, and policy constraints. Return-value details are correctly omitted since an output schema exists.

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 description coverage is 100%, so the baseline is 3; the description adds real value on top by explaining the file_path semantics (prefer an existing path or one returned by the upload-URL endpoint, warning that hotlinked public URLs can fail) and by tying resolution/plan tier to frame-based credit cost. Minor noise: the 'Key options' section cites face_swap_mode and a text prompt, which are not parameters of this tool and could briefly mislead.

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?

The opening sentence states a specific verb and resource ('Create the same Lip Sync you can make in the browser, but programmatically') and clarifies the delivery model (async job returning id + credits_charged). It does not, however, name or contrast itself against the many similar siblings (face_swap_create_video, audio_to_video_create_video, ai_talking_photo_create_talking_photo) — the talking-photo fallback appears only inside the schema, not the description.

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 'Good for' section and the numbered 3-step workflow give clear context for when to reach for this tool, and the MCP guidance explicitly routes the agent to wait_for_video_project or the matching GET /v1/video-projects/{id} poll for the finished result. What is missing is any explicit when-NOT-to-use framing against sibling generation tools (e.g. stills should use AI Talking Photo), which is buried in the schema instead.

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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