Install Jentic One Beta

Connect the Magic Hour API to your agent

Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the Magic Hour API, or any other public or private API you need. You set the rules, the agent never sees your credentials, and every call is logged.

Two steps, two machines. Install the instance in a safe environment, then register your agent from wherever it runs.

Step 1: Jentic One Host machine

# On the machine that will host your Jentic One instance:
curl -fsSL "https://jentic.com/install.sh?src=apis&api=%2Fapis%2Fmagichour.ai%2Fmagichour" | sh

Step 2: Agent machine

# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL "https://jentic.com/install.sh?src=apis&api=%2Fapis%2Fmagichour.ai%2Fmagichour" | sh
jentic register       # connects your agent to your Jentic One instance

Jentic One is in public beta. The setup above keeps your agent separate from the instance, which is what you want before using real credentials: an agent running as the same OS user as Jentic One can read its stored keys directly. Just evaluating? A single local install is fine to start. See the secure deployment guide for the tiers.

Capabilities

What an agent can do with Magic Hour API.

Generate a video from a text prompt or a still image with a chosen model, duration, and aspect_ratio

Lip-sync, face-swap, or translate an existing video into a target_language

Generate, edit, or upscale images by scale_factor and remove image backgrounds

Generate speech with the AI voice generator or clone a voice from an audio asset

GET STARTED

Start building with Magic Hour API

Explore with Jentic One

View OpenAPI Document

Use Cases

Patterns agents use Magic Hour API for, with concrete tasks.

★ AI agent producing social video through Jentic

A marketing agent turns a product brief into a short clip without anyone wiring the Magic Hour client by hand. Through Jentic it searches for 'generate a video from text', loads the text-to-video operation with its input schema, submits a style prompt with end_seconds and an aspect_ratio of 9:16, then polls the video project until its status is complete. The API key is injected at call time.

Call POST /v1/text-to-video with end_seconds 5, aspect_ratio '9:16', and style.prompt 'a dog running on a beach', then poll GET /v1/video-projects/{id} until status is complete and return the download URL

Localising video for new markets

A team with a finished English demo needs versions for other languages. The Magic Hour video translator takes an uploaded video asset, a target_language, and a start and end time, and produces a translated video as a project you poll for status and downloads. Auto subtitles can then be added with the subtitle generator.

Call POST /v1/files/upload-urls for one video item, upload the file, then POST /v1/ai-video-translator with end_seconds, target_language, and the asset path

Product photo cleanup

An online shop needs clean product images on a plain background at higher resolution. Magic Hour removes image backgrounds from an uploaded asset and upscales images by a scale_factor, each returning an image project with status and downloads. A batch job loops these calls over a folder of photos.

For each photo, call POST /v1/image-background-remover with the uploaded asset, then POST /v1/ai-image-upscaler with scale_factor 2, polling GET /v1/image-projects/{id} for each result

Voiceover generation

Explainer clips need narration, and recording takes studio time. The Magic Hour AI voice generator produces speech from a style object, and the voice cloner produces speech in a voice taken from an uploaded audio asset. Results arrive as audio projects with status and download links.

Call POST /v1/ai-voice-generator with a style object holding the narration text, then GET /v1/audio-projects/{id} until complete

Key Endpoints

39 endpoints — the magic hour api generates and edits video, images, and audio with ai models, in beta.

METHOD

PATH

DESCRIPTION

POST

/v1/text-to-video

Generate a video from text

POST

/v1/image-to-video

Generate a video from an image

POST

/v1/lip-sync

Lip-sync a video to audio

POST

/v1/ai-video-translator

Translate a video

POST

/v1/ai-image-generator

Generate images

POST

/v1/image-background-remover

Remove an image background

GET

/v1/video-projects/{id}

Get video status and downloads

POST

/v1/files/upload-urls

Generate asset upload URLs

POST

/v1/text-to-video

Generate a video from text

POST

/v1/image-to-video

Generate a video from an image

POST

/v1/lip-sync

Lip-sync a video to audio

POST

/v1/ai-video-translator

Translate a video

POST

/v1/ai-image-generator

Generate images

POST

/v1/image-background-remover

Remove an image background

GET

/v1/video-projects/{id}

Get video status and downloads

POST

/v1/files/upload-urls

Generate asset upload URLs

Why Jentic?

What agents get from Jentic-routed access to this vendor.

Setup

Wiring Magic Hour by hand means a bearer key, presigned uploads before each job, and polling projects until they render. Through Jentic you install once, import Magic Hour from the API Directory, store the key once, and your agent calls it.

Permission scoping

Magic Hour gives every tool its own path, such as /v1/text-to-video or /v1/image-background-remover, and puts the project id in the URL path, so a rule can bound your agent to the tools it needs and to one project at a time. You choose the operations it may call, so credit-heavy video tools or project deletion are not included unless you add them.

Credential isolation

Your Magic Hour API key is stored once, encrypted, by your own Jentic One instance and injected at execution time. It never enters the agent's prompt, logs, or context.

Intent-based discovery

Agents search Jentic by intent such as 'generate a video from text' or 'remove an image background', and Jentic returns the matching Magic Hour operation with its input schema so the agent calls the right tool without browsing the reference docs.

FAQs

Specific to using Magic Hour API through Jentic.

What authentication does the Magic Hour API use?

The Magic Hour API authenticates with an API key sent as a bearer token in the Authorization header, per its OpenAPI spec. You create the key in the Magic Hour Developer Hub. Through Jentic the key is stored by your own instance and attached at call time, so the agent never sees it.

How do I know when a Magic Hour video is ready?

Each generation call returns a project id. Poll GET /v1/video-projects/{id}, or the image and audio project equivalents, until status moves from queued and rendering to complete, then read the downloads field. A status of error means the job failed.

What are the rate limits for the Magic Hour API?

The OpenAPI spec does not specify rate limits. Generation requests consume account credits that vary by tool, model, and settings; check https://docs.magichour.ai for current limits and pricing.

Is there a Magic Hour MCP server?

You don't need an MCP server to give your agent Magic Hour. Jentic connects it directly from the API Directory: import it, store your API key once, and your agent calls the video, image, and audio tools it needs, discovered on demand rather than loaded into its context up front.

How do I generate an image-to-video clip through Jentic?

Search Jentic for 'turn an image into a video', load the POST /v1/image-to-video operation, and run it with end_seconds and the uploaded image asset, then poll the video project for the result. To run it on your own infrastructure, install Jentic One from its GitHub repo.

Can I limit what my agent is allowed to do with the Magic Hour API?

Yes. For example, a rule that allows POST /v1/image-background-remover, POST /v1/files/upload-urls, and GET /v1/image-projects/{id} lets the agent clean product photos while it cannot start credit-heavy video jobs or delete projects. Jentic logs each call the agent makes.

Magic Hour API

AI ReadinessFoundational (C+)59/100

See full scorecard

Official vendor OpenAPI document · agent-readyMediaVideo Processinghttp (bearer)39 EndpointsREST

For Agents

Generate and edit AI video, images, and audio with Magic Hour: text-to-video, image-to-video, lip sync, face swap, image upscaling, background removal, and voice generation, polled to completion by project id.

Use for: I need to turn a product description into a short vertical video, Generate a video from this still image, Translate my product demo video into Spanish, Remove the background from a set of product photos

Not supported: Does not host or stream finished videos to viewers, edit timelines frame by frame, or publish to social platforms. Use for AI generation and editing of video, images, and audio only.

The Magic Hour API generates and edits video, images, and audio with AI models, in beta. Video tools cover text-to-video, image-to-video, video-to-video, lip sync, face swap, talking photos, auto subtitles, and video translation into a target_language; each job returns an id that you poll for its status, such as queued, rendering, or complete, and its downloads. Image tools generate, edit, upscale, and colorize images, remove backgrounds, and swap faces, heads, or clothes, while audio tools generate speech and clone voices. Generation requests consume account credits, and each project reports credits_charged.

Jentic One on Github View OpenAPI Document

Show dimension breakdown

Foundational Compliance

Base layer of spec validity and structural soundness.

Grade: A+Signals: 4

96%

Lint Results

Aggregated quality score from linter diagnostics, weighted by severity.

100%

Resolution Completeness

Percentage of `$ref` references that resolve successfully.

100%

Specification Validity

Checks whether the API description parses successfully and conforms to its declared specification (e.g., OpenAPI).

100%

Structural Integrity

Structural correctness score based on schema issues using logarithmic dampening.

Developer Experience & Jentic Compatibility

Clarity, completeness, and ingestion readiness for developers and tooling.

Grade: A-Signals: 4

22%

Example Density

How richly the API is illustrated with examples.

100%

Example Validity

Percentage of examples that conform to their schemas.

75%

Response Coverage

Percentage of operations with complete response definitions (success, client error, server error).

100%

Tooling Readiness

Health of API ingestion, bundling, and resolution within Jentic pipelines.

AI-Readiness & Agent Experience

Semantic breadth, depth, and agent comprehension for AI systems.

Grade: FSignals: 4

78%

Description Coverage

Coverage of descriptions across API elements.

Error Standardization

Coverage of RFC 9457 Problem Details for error responses.

OperationId Quality

Coverage, uniqueness, and casing consistency of operationIds for AI inference.

52%

Summary Coverage

Coverage of summaries across operations/tags/info.

Agent Usability

Functional utility, complexity comfort, and AI orchestration readiness.

Grade: A+Signals: 1

94%

Complexity Comfort

Agent comfort level based on API operational and structural complexity.

Security

Trust, risk posture, and security compliance.

Grade: B-Signals: 1

60%

Authentication Strength

Average quality of security schemes based on authentication method strength (weakest link for OAuth2).

AI Discoverability

Findability, semantic richness, and reasoning readiness.

Grade: B+Signals: 1

67%

Descriptive Richness

Clarity and depth of descriptions across API elements.

Connect the Magic Hour API to your agent

Capabilities

Start building with Magic Hour API

Use Cases

Key Endpoints

Why Jentic?

Related APIs

FAQs

Magic Hour API

Jentic AI Readiness Score

Magic Hour API

Foundational Compliance

Lint Results

Resolution Completeness

Specification Validity

Structural Integrity

Developer Experience & Jentic Compatibility

Example Density

Example Validity

Response Coverage

Tooling Readiness

AI-Readiness & Agent Experience

Description Coverage

Error Standardization

OperationId Quality

Summary Coverage

Agent Usability

Complexity Comfort

Security

Authentication Strength

AI Discoverability

Descriptive Richness