Magic Hour

Character Replace

character_replace_create_video

What this API does

Create the same Character Replace 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 character replace 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 character replace 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.	Character Replace - dateTime
`model`	No	Model to use. Defaults to `wan-animate`. * `wan-animate`: 480p, 720p. Supports `points` subject selection. * `kling-3.0`: 720p, 1080p. Clips of 3–10 seconds in `replace` mode or 3–30 seconds in `animate` mode. Picks the main person automatically, so `points` are rejected.	wan-animate
`style`	No	Optional style controls for replace vs animate mode and subject selection.
`assets`	Yes	Source video and reference character image for the job.
`resolution`	No	Output video resolution. Must be supported by `model`. Defaults to the lowest resolution available on your plan for that model.
`end_seconds`	Yes	End time of your clip (seconds). Must be greater than start_seconds.
`start_seconds`	No	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.

Changed5 schema fields changedSep 29, 2026

addedInput schema / properties / model

Added value: +{
+  "default": "wan-animate",
+  "description": "Model to use. Defaults to `wan-animate`.\n\n* **`wan-animate`**: 480p, 720p. Supports `points` subject selection.\n* **`kling-3.0`**: 720p, 1080p. Clips of 3–10 seconds in `replace` mode or 3–30 seconds in `animate` mode. Picks the main person automatically, so `points` are rejected.",
+  "enum": [
+    "wan-animate",
+    "kling-3.0"
+  ],
+  "example": "wan-animate",
+  "type": "string"
+}

changedInput schema / properties / resolution / description

Previous value: -"Output video resolution. Defaults to 480p, the lowest resolution available on your plan."New value: +"Output video resolution. Must be supported by `model`. Defaults to the lowest resolution available on your plan for that model."

changedInput schema / properties / resolution / enum

Previous value: -[
-  "480p",
-  "720p"
-]New value: +[
+  "480p",
+  "720p",
+  "1080p"
+]

changedInput schema / properties / style / properties / points / description

Previous value: -"On-frame markers for manual subject selection. Required when `selection_mode` is `point`. Ignored when `selection_mode` is `auto` or omitted."New value: +"On-frame markers for manual subject selection. Required when `selection_mode` is `point`. Ignored when `selection_mode` is `auto` or omitted. Rejected for models without subject selection (supported by `wan-animate`)."

changedInput schema / properties / style / properties / selection_mode / description

Previous value: -"How to locate the subject in the source video. `auto` detects a person automatically. `point` uses your `points` to mark the subject. Defaults to `auto`."New value: +"How to locate the subject in the source video. `auto` detects a person automatically. `point` uses your `points` to mark the subject and is supported by `wan-animate`. Defaults to `auto`."

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

A3.9/5.0

Behavior4/5

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

Annotations cover the safety profile (readOnlyHint=false, destructiveHint=false, openWorldHint=true), and the description adds substantial context beyond them: async job semantics, immediate return of id plus credits_charged, credit billing based on rendered frames, and polling/status transitions. It also adds an important usage restriction (own likeness only, no impersonation/minors).

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?

The header-based structure is front-loaded and scannable, but it is long and includes promotional material ('For detailed examples, see the product page', 'Good for' bullets) that does not help an agent select or invoke the tool. The operational guidance in the MCP section is dense and useful, but the marketing prose dilutes it.

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, nested-schema tool this covers everything an agent needs: the upload prerequisite and file_path convention, the create-then-poll workflow, the terminal statuses, and where downloads appear. The output schema exists, so it need not explain return shapes, and the extra legality/safety note is a bonus.

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 schema already documents all seven parameters with examples, enums, and nested structure; the baseline is 3. The description's 'Key options' section adds plan-tier context (free users limited in resolution) but also mentions fields like face_swap_mode that are not in this schema, which is mildly misleading rather than additive.

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 description states a specific verb+resource ('Create the same Character Replace you can make in the browser, but programmatically') and names the key options, so an agent knows this produces a character-replacement video. It does not explicitly contrast itself with close siblings like face_swap_create_video or body_swap_create_image, so the agent must infer the distinction from the name alone.

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?

It gives clear triggering contexts ('Automation and batch processing', 'Adding character replace into apps, pipelines, or tools') and, in the MCP guidance, explicitly routes to the wait_for_video_project helper for the finished result. No exclusionary guidance against sibling video-generation tools is given, but the positive usage framing is concrete.

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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