Supercharge your AI with Kapwing. Automate Video Rendering from JSON Definitions

Q: How can I check if my video render is finished?

You can use the getrenderstatus tool by providing your unique Render ID. The agent will return the current status (e.g., 'completed') and the download URL if it's ready.

Q: Can I start a new render using a JSON project definition?

Yes! Use the createrender action. You just need to provide the project object containing dimensions and layers. You can also specify a webhookUrl for automated notifications.

Q: Is it possible to see a history of all my renders?

Absolutely. The listrenders tool fetches all renders associated with your authenticated account, allowing the AI to summarize or find specific past projects.

Q: After running listrenders, what is the next step to check a specific render's status?

First, use listrenders to get the unique ID for your asset. Then, pass that specific ID into the getrenderstatus tool to track its progress or retrieve the download link.

Claude

ChatGPT

Cursor

Gemini

Windsurf

VS Code

JetBrains

Vercel

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

Connect to your AI in seconds.

Kapwing automates video and image rendering pipelines directly from your agent. Instead of manual uploads or clicking through web interfaces, you define complex media projects using structured JSON data.

Your AI client initiates the render job, monitors its progress in real-time, and retrieves final assets—all without leaving your coding environment.

What your AI can do

Create render

Starts the render process for a new project based on provided dimensions and layers.

Get render status

Checks the current status of a specified asset ID and returns the download URL if processing finished.

List renders

Retrieves an account history containing all previously created media assets.

Initiate complex renders

Send a project definition (including dimensions, text, and video layers) to start an automated render job.

Check job status

Get the current processing state of any specific media asset ID and download link when complete.

Review asset history

List all previously created and archived renders associated with your account.

Ask an AI about this

Compatible AI Apps

OAuth 2.0 Compatible

Claude

ChatGPT

Cursor

Gemini

VS Code

JetBrains

Vercel

Zendesk

+ any other MCP app

Included with Plan

Waiting for input…

AI Agent

Kapwing Media Tools (3)

These tools let your agent create dynamic video and image assets by defining project parameters and tracking the lifecycle of those renders.

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 Kapwing on Vinkius

Create Render

Starts the render process for a new project based on provided dimensions and layers.

Get Render Status

Checks the current status of a specified asset ID and returns the download URL if...

List Renders

Retrieves an account history containing all previously created media assets.

Connect to your AI in seconds. Security and governance baked right in.

Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.

Claude AI

Open Claude Settings

Go to claude.ai, click your profile icon, then navigate to Customize → Connectors.

Add Custom Connector

Click the "+" button and select Add custom connector. Paste your Vinkius endpoint URL:

https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp

Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. For OAuth-protected servers, expand Advanced settings to add credentials.

Start a conversation

Open a new chat. The Kapwing integration is available immediately — no restart needed.

Antigravity

Configure Agent Environment

Open your Antigravity agent's workspace configuration or mcp-servers.json file.

Bind the Endpoint

Add the Vinkius endpoint URL to your agent's MCP connections list:

"mcp_servers": {
  "kapwing": {
    "serverUrl": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
  }
}

Provide your secure token in place of [YOUR_TOKEN_HERE] to ensure your agent requests are authenticated.

Execute

Start your Antigravity session. The agent will autonomously discover and utilize the Kapwing tools with full Vinkius guardrails applied.

VS Code Copilot

⚡

One-Click Install (Recommended)

In your Vinkius Dashboard, simply click the Add to VS Code button for this server. We'll automatically configure your local workspace.

Or configure manually

Open MCP Settings

Open VS Code, press Ctrl/Cmd + Shift + P, and search for GitHub Copilot: MCP Servers.

Add Server Config

Add the Vinkius endpoint configuration to your mcp-servers.json file:

"kapwing": {
  "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
}

Ensure you replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.

LangChain

Install Dependencies

Install the LangChain MCP adapters for your environment:

pip install langchain-mcp-adapters

Connect the Server

Use the SSEClient in LangChain to connect to the Vinkius managed endpoint:

from langchain_mcp_adapters.client import SSEClient

# Connect to Vinkius
client = SSEClient(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
tools = client.get_tools()

CrewAI

Define the Tool

Load the Vinkius MCP tools into your CrewAI agents:

from crewai import Agent
from mcp_crewai import MCPTool

# Connect securely to Vinkius
vinkius_tools = MCPTool(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

# Assign to Agent
researcher = Agent(
    role='Data Researcher',
    tools=vinkius_tools.get_all()
)

Execute Task

Run your CrewAI process. The agent will autonomously route tasks to the Vinkius managed server.

Choose How to Get Started

Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.

Build Your Own

Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.

Import from OpenAPI, Swagger, or YAML specs
Create Agent Skills with progressive disclosure
Deploy to edge with MCPFusion framework
Built in DLP, auth, and compliance on every call
Real time usage dashboard and cost metering
Publish to catalog or keep private

Start building

Make Your AI Do More

Start with Kapwing, then connect any of our 5,000+ other servers whenever your AI needs more. One click, no limits.

Use this MCP plus 5,000+ others, all in one place
Add new capabilities to your AI anytime you want
Every connection is secured and compliant automatically
Track usage and costs across all your servers
Works with Claude, ChatGPT, Cursor, and more
New servers added to the catalog every week

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Kapwing. 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.

VINKIUS INFRASTRUCTURE

Cloud Hosted

Managed infra

V8 Isolated

Sandboxed per request

Zero-Trust Proxy

No stored credentials

DLP Enforced

Policy on every call

GDPR Compliant

EU data residency

Token Compression

~60% cost reduction

Your data is protected. See how we built it.

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 3 powerful capabilities that interface natively with Claude, ChatGPT, Cursor, and other compatible AI platforms. No middleware. No custom integration required.

Setting up automated video pipelines is usually painful.

Today, if you need to generate 50 localized video ads, you're either logging into the web interface and hitting 'Generate' fifty times, or you are writing complex scripting that handles file uploads and then manually parsing status codes. The process is fragmented: one step for input, another for waiting, and a third for downloading.

With this MCP, your agent treats video rendering like any other API call. You send the full project definition in JSON, initiate the job, and let the system handle the rest of the state machine. You get immediate access to the final asset URL once it clears processing.

Kapwing MCP delivers reliable media asset creation.

The need for `list_renders` disappears manual searching through folders and checking old project names. You have a single, auditable log of every render job you've ever created or checked on.

This means your pipeline isn't just functional; it's verifiable. Every asset has a documented history right where you expect it.

Support 24/7 support@vinkius.com ↗

Security Vinkius Trust Center ↗

SLA Service Level Agreement ↗

Report Listing Send Report ↗

What your AI can actually do with this

You're automating video production via natural conversation. This MCP lets your agent handle the entire rendering workflow for you, from project definition to final file download. You feed it a JSON structure describing layers, text placements, and dimensions. It kicks off the render job and provides a unique ID for tracking.

Your agent then polls that status until the asset is ready, giving you immediate notification or the direct URL to the completed media. Need to check what assets you've already made? You can list all previous renders in one shot. This saves time when scaling content production—whether you’re building a feature into an app or just churning out localized social media videos.

It brings professional media rendering power into your command line, and Vinkius makes connecting it to any of your agents simple.

Built · Hosted · Managed by Vinkius Kapwing-MCP - Automate Video Rendering and Asset Management

Server ID 019e38b4-411b-72d7-b7dc-9456603ba68e

Vinkius Inspector

Compliance Grade A+

Score 100/100

Report View Report ↗

Here's how it actually works

The bottom line is, your AI client manages the entire state machine for you; you just tell it what media to build.

Connect the MCP to your preferred AI client and provide the required Kapwing API Key.

Tell your agent what media you need. The agent sends a JSON project definition using create_render.

Your agent tracks progress by calling get_render_status until the asset is marked 'Complete,' then retrieves the download URL.

What Changes When You Connect

Start renders with create_render using structured JSON. You don't need to manually upload files or set dimensions; you just pass the data.

Track job progress reliably. Use get_render_status to poll for updates, so your agent knows exactly when the asset is ready for download.

Maintain a complete record of all work. Run list_renders anytime to see every project generated and manage your media history in one place.

Write content pipelines that scale. Instead of repeating manual steps for different markets, define template renders once and automate the loop.

Integrate rendering into code. Developers can treat video generation like any other backend service call, making complex assets part of a simple workflow.

See it in action

01 01

Need to update 50 social media ads with new branding?

The Content Manager asks the agent: 'Run create_render five times, changing only the text layer and image asset for each market.' The system processes the JSON definitions, starts all jobs, and then polls using get_render_status until every ad is ready.

02 02

Building a new feature that needs dynamic video assets.

The developer uses the MCP to call create_render when the user clicks 'Generate Video Preview.' The agent monitors the status, and once finished, it passes the download URL back to the frontend for display.

03 03

Auditing all past media output.

The ops team runs list_renders to generate a manifest of every asset created in the last month. This helps them identify which templates are being used most often and where assets were stored.

The honest tradeoffs

Treating renders like simple file uploads

Anti-pattern

Manually downloading a video, opening it in an editor, adding text, and re-uploading it. This is slow and doesn't scale.

The Fix

Define the entire composition (video background, layers, text) inside a JSON payload and run create_render. Your agent handles the complex assembly.

Not knowing if a render finished

Anti-pattern

Calling a job creation tool (create_render) and then assuming it worked. The script fails because the status was never checked.

The Fix

Always follow up create_render with a loop that calls get_render_status until you receive a 'Completed' state.

When It Fits, When It Doesn't

Use this MCP if your core bottleneck is media asset generation. Specifically, if you need to programmatically define complex visual projects (multiple layers, fixed dimensions) and manage the asynchronous queueing process. You must use create_render followed by polling with get_render_status. Don't use this if you only need simple image resizing; those tools are better suited for basic file manipulation. Also, don't rely on it for content planning—it just makes the asset. For that, use a dedicated knowledge base or writing tool instead.

Questions you might have

How can I check if my video render is finished? +

You can use the get_render_status tool by providing your unique Render ID. The agent will return the current status (e.g., 'completed') and the download URL if it's ready.

Can I start a new render using a JSON project definition? +

Yes! Use the create_render action. You just need to provide the project object containing dimensions and layers. You can also specify a webhookUrl for automated notifications.

Is it possible to see a history of all my renders? +

Absolutely. The list_renders tool fetches all renders associated with your authenticated account, allowing the AI to summarize or find specific past projects.

How do I authenticate my account when using list_renders or create_render? +

You must provide your Kapwing API Key in the initial setup. This key authorizes every operation, whether you're listing existing assets or starting a brand new render job.

If my project JSON structure is incorrect, how does create_render handle the error? +

The MCP will return a specific error code detailing exactly what went wrong. You need to check the API documentation for required formatting details regarding dimensions or layer definitions.

Can I set up webhooks when managing my media assets? +

Yes, you can provide a specific URL for notifications. This means Kapwing sends an alert directly to your endpoint the second processing finishes, eliminating the need for manual status checks.

Does create_render support multiple video and text layers simultaneously? +

Yes, the project definition handles complex layering within one call. You define dimensions, background videos, and any number of text or visual overlays in a single JSON payload.

After running list_renders, what is the next step to check a specific render's status? +

First, use list_renders to get the unique ID for your asset. Then, pass that specific ID into the get_render_status tool to track its progress or retrieve the download link.

Connect to your AI in seconds.

Create render

Get render status

List renders

Kapwing Media Tools (3)

Make your AI actually useful.

Create Render

Get Render Status

List Renders

Connect to your AI in seconds. Security and governance baked right in.

Claude AI

Open Claude Settings

Add Custom Connector

Start a conversation

Claude Code

Open your terminal

Add the MCP Server

Start coding

Cursor

One-Click Install (Recommended)

Open Cursor Settings

Add New Server

Use in Composer

Antigravity

Configure Agent Environment

Bind the Endpoint

Execute

VS Code Copilot

One-Click Install (Recommended)

Open MCP Settings

Add Server Config

Windsurf

One-Click Install (Recommended)

Open Windsurf Settings

Add Server Endpoint

LangChain

Install Dependencies

Connect the Server

CrewAI

Define the Tool

Execute Task

Choose How to Get Started

Build Your Own

Make Your AI Do More

Works with Claude, ChatGPT, Cursor, and more

Setting up automated video pipelines is usually painful.

Kapwing MCP delivers reliable media asset creation.

What your AI can actually do with this

Here's how it actually works

Who is this actually for?

What Changes When You Connect

See it in action

Need to update 50 social media ads with new branding?

Building a new feature that needs dynamic video assets.

Auditing all past media output.

The honest tradeoffs

Treating renders like simple file uploads

Not knowing if a render finished

When It Fits, When It Doesn't

Questions you might have