CaptionHub MCP for AI. Manage sub-titles and video localization from your agent.
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CaptionHub manages your entire video localization pipeline. Use this MCP to track projects, trigger AI auto-transcription for videos, and approve subtitle sets directly from any connected agent.
It handles the full caption lifecycle—from initial project creation to final export.
What your AI can do
Approve captions
Marks a specific set of captions as approved for use.
Archive project
Removes an entire video localization project permanently from the system.
Create project
Sets up a brand new captioning project for incoming video content.
List all video captioning projects or retrieve specific metadata for one project ID.
Trigger AI auto-transcription on a selected video asset within your workspace.
Approve, archive, or modify caption sets for specific languages using simple commands.
Retrieve the direct download link needed to export finished captions in various formats.
Monitor active webhooks and project statuses to ensure your localization pipeline runs smoothly.
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CaptionHub: 10 Tools for Content Workflow Management
These tools let you programmatically handle every stage of video captioning, from creating a new project to archiving old data.
Make your AI actually useful.
Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.
Start using CaptionHub on VinkiusApprove Captions
Marks a specific set of captions as approved for use.
Archive Project
Removes an entire video localization project permanently from the system.
Create Project
Sets up a brand new captioning project for incoming video content.
Export Captions
Generates and retrieves the final download URL for finished captions in various...
Get Account Info
Retrieves basic information about your connected CaptionHub account.
Get Project Details
Pulls specific details and status reports for one video project by its ID.
List Projects
Returns a list of every active video captioning project you manage.
List Webhooks
Shows all the webhook endpoints currently set up to monitor your projects.
Transcribe Video
Starts an AI process to automatically transcribe a video asset for a specific...
Update Project
Changes metadata, like the title or target language, on an existing project.
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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by CaptionHub. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
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Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This connection provides 10 powerful capabilities that interface natively with Claude, ChatGPT, Cursor, and other compatible AI platforms. No middleware. No custom integration required.
The Subtitle Approval Bottleneck
Today, managing captions feels like a scavenger hunt. You're constantly logging into the project portal just to check if the French subtitles are ready for review. Then you might have to switch tabs to see if the German metadata got updated correctly, and copy-pasting IDs between sheets is unavoidable.
With this MCP, checking statuses is instantaneous. Your agent handles the dashboard work. You ask it to pull project details or list all projects in one go. The status updates right there in your conversation window—no clicking required.
Workflow Control with CaptionHub
You eliminate the manual steps of initiating transcription, checking webhook logs, or generating final download links. You can trigger a new auto-transcription via `transcribe_video` and then use natural language to approve the resulting captions using `approve_captions`, all without touching a web UI.
What’s different now is control. The MCP lets your agent manage the entire asset lifecycle, ensuring that when you're done with the project, the final files are one simple command away via `export_captions`.
What your AI can actually do with this
Need to manage subtitles across multiple languages? This MCP connects CaptionHub to your agent so you can handle video localization workflows without leaving your toolchain. You'll start by listing all projects and checking their metadata, figuring out exactly what needs work. From there, you can trigger AI-powered transcription directly against a video asset in the workspace.
Once the transcript is ready, you use natural conversation to approve or archive specific caption sets for different languages. If you need final files, retrieving export links is simple. Everything runs through your agent, making sure every project status and webhook is monitored automatically. This kind of deep control over complex content workflows is what Vinkius makes possible, letting you manage the entire subtitle process conversationally.
019d7569-8059-72d5-9cc3-db39b86a63bd Here's how it actually works
The bottom line is that your agent treats CaptionHub like another built-in function, letting you manage complex video assets through conversation alone.
First, connect your API key to the MCP. This gives your agent access to all CaptionHub functions.
Next, use natural conversation—like 'List my current video projects'—to pull up project statuses and details.
Finally, when you need transcripts or export links, simply ask your agent to perform the action for a specific ID.
Who is this actually for?
This MCP is for localization managers and content producers who are sick of clicking through dozens of tabs just to check if a subtitle file is ready. It's for the person whose job requires juggling video assets, multiple languages, and strict approval workflows.
Uses this MCP to quickly list project metadata or trigger transcriptions without having to log into the main dashboard.
Requests export links for finished captions and monitors approval stages directly from their agent's command line.
Orchestrates the subtitle workflow, verifying asset metadata and managing caption approvals using natural language commands.
What Changes When You Connect
You instantly check project status. Instead of jumping between tabs to see if a job is done, you just ask your agent to list all projects or get details for one using get_project_details.
Transcription happens on demand. Triggering auto-transcription via the transcribe_video tool means you don't wait until a batch process runs; you start it exactly when you need it.
Approvals are conversational. Use natural language to approve or archive captions. No more clicking through multiple approval screens just to mark something 'Done'.
Exporting is simple. Need the SRT file? The export_captions tool gets you a direct download link immediately, bypassing complex download menus.
It keeps your pipeline visible. By monitoring webhooks and project statuses, you know if an automated step failed or succeeded without manual checks.
See it in action
The handover review
A video editor finishes a draft in Spanish (ID: proj_123). Instead of emailing the Localization Manager to check status, they ask their agent to get_project_details for proj_123. The manager gets the status and confirms it's ready to be reviewed.
Mass cleanup
A project is canceled because the source video was pulled. Instead of manually finding and deleting records, the content producer runs archive_project on the relevant ID to clean up the system immediately.
Localization audit
The manager needs a list of all projects that are currently set up for German translation. They run list_projects, which returns detailed metadata, allowing them to quickly see exactly what’s active and where the assets are.
Final delivery prep
The team just finished all reviews on a project. The content producer asks their agent for the export link using export_captions, receiving the direct URL needed to hand off the final files.
The honest tradeoffs
Manual status checks
Checking project statuses requires logging into the web portal, navigating to the Project Dashboard, and clicking through multiple tabs until you find the current status of a single asset.
Use your agent. A simple command like 'What is the status for proj_xyz?' using get_project_details gets you that information instantly without leaving your workflow.
Confusing approval stages
The team needs to approve captions, but they aren't sure if the current set is ready for review or if it needs to be archived first.
Use approve_captions when the content passes quality checks. If a project is finished and shouldn't appear in active lists, use archive_project.
Forgetting the ID
You know you need to update a project, but you don't remember its unique metadata or if it was listed as 'Video Project' or 'Localization Job'.
Always start by running list_projects. This gives you all the IDs and names you need before attempting any change like using update_project.
When It Fits, When It Doesn't
Use this MCP if your workflow centers around managing content through distinct, multi-stage processes (e.g., draft -> review -> approve -> export). You need it when the process involves multiple states and required sign-offs. Don't use it if you just need to store text or manage simple documents; a standard document storage tool is better for that. However, don't rely on it for live streaming content—this MCP focuses purely on asynchronous video asset localization. If your core bottleneck is tracking the passage from raw video file to final subtitle export, this MCP solves it.
Questions you might have
How do I check all my video projects using list_projects? +
You simply ask your agent to use list_projects. It returns a full manifest of every active project ID and its current status, so you know exactly what's in the system.
Can I approve captions using approve_captions? +
Yes. You direct your agent to use approve_captions along with the specific language code. This officially marks the set as approved for use by everyone else on the team.
What is the best way to get a new project started? Use create_project. +
To start fresh, you tell your agent to create_project. This initializes all necessary metadata and gives you a clean slate for the video content.
Does transcribe_video only work on finished videos? +
No. You trigger transcribe_video directly from your workspace against the asset ID. It runs AI auto-transcription to get you a usable transcript for review immediately.
If I need detailed metadata for a single video, what does `get_project_details` provide? +
It gives you comprehensive data on one specific project. You can pull details like source/target languages or assigned owners without listing all projects first.
How do I manage webhooks or monitor status changes using `list_webhooks`? +
You use list_webhooks to see every active webhook. This lets your agent confirm which endpoints are monitoring project statuses, ensuring reliable workflow automation.
What format can I expect when I call `export_captions`? +
You receive a specific download URL for the finished captions. The link is ready to pull the data in various standard formats, like SRT or VTT files.
If I need to modify the details of an existing project, how does `update_project` work? +
You use update_project to change metadata for a running job. This function lets you adjust things like ownership or target language without recreating the entire workflow.
Can I trigger auto-transcription for a video using the agent? +
Yes! Use the transcribe_video tool with the Project ID. Your agent will trigger CaptionHub's AI engine to start transcribing the video content instantly.
How do I get the download link for finished subtitles? +
Simply ask the agent to export_captions and provide the Project ID and the language code (e.g., 'fr' or 'es'). It will return the export URL for your finished caption set.
Does the integration allow approving captions via the workspace? +
Yes. Use the approve_captions tool with the Project ID and Language. This will mark the specific caption set as approved in your CaptionHub workflow.
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