How to Use the Vadoo AI MCP in Cursor

Q: How does Vadoo AI integrate with Cursor?

You set up the server in your .cursor/mcp.json file, pointing it to the endpoint. Once configured, Cursor's agent mode lets you call tools like vadooaigeneratevideo directly while writing code.

Q: Can Cursor use Vadoo AI for status checks?

Yes. You can write functions that call vadooaicheckgenerationstatus. This allows your code to pause and wait for confirmation on a background media job, making the process robust.

Build code that uses Vadoo AI video generation directly in Cursor, without leaving your editor.

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Connect Vadoo AI MCP to Cursor

Create your Vinkius account to connect Vadoo AI to Cursor and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Vadoo AI with Cursor

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Generate Video from Prompt

Writing a script for a new feature? Use `vadooai_generate_video` to prototype the media. Your agent calls this tool and injects the live video URL directly into the code block you're working on. It's real data, not stubs. This lets your AI client test content generation right where you write API calls or markdown documentation.

Generate AI Podcasts

Need to document a process that involves an audio component? Call `vadooai_generate_podcast` within your code. The live response gives you the necessary asset information, so you can write the file handling logic immediately. It keeps your entire workflow—from coding to media integration—contained in Cursor.

Create Short Video Clips

If you need to process a video before writing the final build step, use `vadooai_create_clips`. This tool takes an existing video and breaks it into usable chunks. The live API response gives you the necessary file identifiers right in your editor. It's powerful because the AI client can write code that handles the output of this process immediately.

Setup guide

Set up Vadoo AI MCP in Cursor

Prerequisites

Cursor installed (macOS, Windows, or Linux)
Active Vinkius subscription with a valid endpoint token

1

Open MCP Settings

Go to Cursor Settings → MCP or open the Command Palette (Cmd+Shift+P / Ctrl+Shift+P) and search for "MCP: Add Server".
2

Add the Vadoo AI MCP

Cursor will create or open .cursor/mcp.json in your project root. Paste the JSON snippet on the right. Replace [YOUR_TOKEN_HERE] with your endpoint token from cloud.vinkius.com.
3

Enable Agent mode

Open Composer (Cmd+I / Ctrl+I) and switch to Agent mode using the dropdown at the top. MCP tools are only available in Agent mode.
4

Verify the connection

Ask Cursor something like "List my recent Vadoo AI transactions." If the MCP tools are loaded correctly, Cursor will call the Vadoo AI tools automatically. You can also check Settings → MCP for a green status indicator.

.cursor/mcp.json

{
  "mcpServers": {
    "vadoo-ai-mcp": {
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}

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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 Vadoo AI. 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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Common questions about Vadoo AI MCP in Cursor

You set up the server in your `.cursor/mcp.json` file, pointing it to the endpoint. Once configured, Cursor's agent mode lets you call tools like `vadooai_generate_video` directly while writing code.

The primary input is a completed video asset. The tool reads the visual media to generate text transcripts, which are then provided back through your agent's live response stream.

Yes. You can write functions that call `vadooai_check_generation_status`. This allows your code to pause and wait for confirmation on a background media job, making the process robust.

The server documentation provides rate limits. For best results, ensure you handle asynchronous calls properly within your code to avoid hitting those constraints repeatedly.

It handles video media assets and associated text data. This includes prompts, generated captions, and final podcast audio files.

Use it with your favorite AI tools

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