Magic Hour

by ai.magichour.mcp

video_projects_retrieve_details

Check the progress of a video project. The downloads field is populated after a successful render.

Statuses

queued — waiting to start
rendering — in progress
complete — ready; see downloads
error — a failure occurred (see error)
canceled — user canceled
draft — not used

MCP guidance:

Use this after a create tool to poll job status. When status is complete, surface the downloads URLs to the user; if status is error, surface the error message.
Each downloads[n].url is already the full signed download URL. Use it exactly as returned. Do not shorten it, strip query parameters, or append expires_at onto the URL string.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`id`	Yes	Unique ID of the video project. This value is returned by all of the POST APIs that create a video.

Output Schema

TableJSON Schema

Name	Required	Description
`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.
`fps`	Yes	Frame rate of the video. If the status is not 'complete', the frame rate is an estimate and will be adjusted when the video completes.
`name`	Yes	The name of the video.
`type`	Yes	The type of the video project. Possible values are ANIMATION, AUTO_SUBTITLE, VIDEO_TO_VIDEO, FACE_SWAP, TEXT_TO_VIDEO, IMAGE_TO_VIDEO, LIP_SYNC, TALKING_PHOTO, AVATAR, VIDEO_UPSCALER, VIDEO_EDITOR, CHARACTER_REPLACE, VIDEO_COLORIZER, VIDEO_COLOR_GRADER, VIDEO_TRANSLATOR, MUSIC_VIDEO, EXTEND, AUDIO_TO_VIDEO, VIDEO_EXPANDER, UGC_AD
`error`	Yes	In the case of an error, this object will contain the error encountered during video render
`width`	Yes	The width of the final output video. A value of -1 indicates the width can be ignored.
`height`	Yes	The height of the final output video. A value of -1 indicates the height can be ignored.
`status`	Yes	The status of the video. - `draft` - the project was created but has not been submitted for rendering - `queued` - the job is waiting for an available server - `rendering` - the job is being processed; the `video.started` webhook event fires when rendering begins - `complete` - the job finished successfully; fires `video.completed` - `error` - the job failed during processing; fires `video.errored` - `canceled` - the job was manually canceled (for example from the Magic Hour web app) Note: `rendering`, `complete`, and `error` have matching webhook events; `canceled` does not - a canceled job emits no webhook event, so poll this endpoint to detect cancellation.
`enabled`	Yes	Whether this resource is active. If false, it is deleted.
`downloads`	Yes
`created_at`	Yes
`end_seconds`	Yes	End time of your clip (seconds). Must be greater than start_seconds.
`start_seconds`	Yes	Start time of your clip (seconds). Must be ≥ 0.
`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. Dates show when Glama detected each change.

Changed1 schema field changedSep 5, 2026

changedOutput schema / properties / type / description

Previous value: -"The type of the video project. Possible values are ANIMATION, AUTO_SUBTITLE, VIDEO_TO_VIDEO, FACE_SWAP, TEXT_TO_VIDEO, IMAGE_TO_VIDEO, LIP_SYNC, TALKING_PHOTO, AVATAR, VIDEO_UPSCALER, VIDEO_EDITOR, CHARACTER_REPLACE, VIDEO_COLORIZER, VIDEO_TRANSLATOR, MUSIC_VIDEO, EXTEND, AUDIO_TO_VIDEO, VIDEO_EXPANDER, UGC_AD"New value: +"The type of the video project. Possible values are ANIMATION, AUTO_SUBTITLE, VIDEO_TO_VIDEO, FACE_SWAP, TEXT_TO_VIDEO, IMAGE_TO_VIDEO, LIP_SYNC, TALKING_PHOTO, AVATAR, VIDEO_UPSCALER, VIDEO_EDITOR, CHARACTER_REPLACE, VIDEO_COLORIZER, VIDEO_COLOR_GRADER, VIDEO_TRANSLATOR, MUSIC_VIDEO, EXTEND, AUDIO_TO_VIDEO, VIDEO_EXPANDER, UGC_AD"

First observedSep 1, 2026

TDQS

A4.3/5.0

Behavior5/5

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

With no annotations, the description carries the full behavioral disclosure burden. It covers status semantics, when downloads gets populated, and the crucial fact that download URLs are already signed and must not be modified. This is strong, actionable transparency.

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

Conciseness5/5

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

The description is front-loaded with the core purpose, followed by a compact status table and MCP guidance. Every sentence earns its place, and the structure makes the polling workflow easy to follow.

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?

The description fully equips an agent to poll correctly: it explains statuses, what to surface on completion, what to do on error, and how to handle download URLs. An output schema exists, so the description need not re-explain return values.

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 coverage is 100%, so the id parameter is already well documented as the unique video project ID returned by creation APIs. The description adds contextual usage guidance but no new parameter-level semantics beyond what the schema provides.

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 clearly states the tool checks the progress of a video project and explains the status lifecycle. It does not explicitly differentiate itself from sibling tools like wait_for_video_project, so it stops short of full sibling differentiation.

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 MCP guidance explicitly says to use this tool after a create tool to poll job status, and tells the agent what to do for complete and error statuses. However, it does not mention when not to use it or compare it to polling helper siblings, so it lacks exclusions and alternatives.

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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TDQS

A3.9/5.0

Disambiguation3/5

Most tools are differentiated by product-specific prefixes (e.g., lip_sync, text_to_video, image_upscaler), but the set contains many overlapping create_image/create_video tools, and generic editors like ai_image_editor_create_image and ai_video_editor_create_video blur boundaries with their more specific counterparts. Face/body swapping tools also occupy a similar conceptual space, requiring careful description reading to avoid misselection.

Naming Consistency4/5

Names generally follow a descriptive snake_case pattern of feature plus action (e.g., text_to_video_create_video, image_projects_delete, wait_for_image_project). Minor inconsistencies like ai_face_editor_edit_image versus the dominant create_image suffix, and the mixed ai_ prefix usage across tools, prevent a perfect score.

Tool Count2/5

44 tools is a large surface for an MCP server, even for a broad media-generation API. The count exceeds the 25+ threshold and creates a heavy selection burden, especially with over a dozen create tools for images and videos.

Completeness4/5

The surface covers the full create-to-download workflow for image, video, and audio: creation, status polling, wait helpers, fetch helpers, delete, and asset upload support. Minor gaps include no list/cancel endpoints and no general project search, but agents can complete core tasks without dead ends.

Resources

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