How to Use the Vadoo AI MCP in VS Code Copilot

Q: How do I configure Vadoo AI using VS Code Copilot?

You define it organization-wide in .vscode/mcp.json and commit that file to your repository. This makes the MCP Server available instantly for every developer on the team.

Q: Does Vadoo AI handle video captions through VS Code Copilot?

Yes, you can use vadooaigeneratecaption. The agent reads a completed video and outputs structured caption data that integrates directly into your documentation files.

Q: Does Copilot support checking video status with Vadoo AI?

Yes, you can prompt the agent to call vadooaicheckvideostatus. This allows your team's code to reliably check for final media details after an asynchronous job finishes.

Manage team content pipelines using Vadoo AI's MCP Server via VS Code Copilot Chat.

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Connect Vadoo AI MCP to VS Code Copilot

Create your Vinkius account to connect Vadoo AI to VS Code Copilot 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 VS Code Copilot

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Claude

Perplexity

Generate Video from Prompt

Copilot Chat can call `vadooai_generate_video` to create sample media for documentation or demos. The result is an asset ID that the agent writes into your shared `.vscode/mcp.json`, making it visible to every developer on the team. This means everyone gets access to the content generation capabilities without manual setup.

Check Video Status

Team workflows need reliable status checks. Use `vadooai_check_generation_status` via Copilot Chat. The agent reports back on job progress, letting your team know if the video pipeline is running or finished. Commit these calls to ensure every developer uses the same operational standard.

Generate AI Podcasts

Need a quick audio asset for a tutorial? `vadooai_generate_podcast` lets you prototype it using natural language prompts. The agent handles this, and the resulting metadata is saved in your project's MCP configuration. This centralizes media creation into the shared codebase.

Setup guide

Set up Vadoo AI MCP in VS Code Copilot

Prerequisites

VS Code 1.99 or later with GitHub Copilot extension
Active Vinkius subscription with a valid endpoint token

1

Open MCP configuration

Open the Command Palette (Cmd+Shift+P / Ctrl+Shift+P) and run "MCP: Add Server". Select HTTP (Streamable) as the server type. VS Code will create .vscode/mcp.json in your workspace.
2

Add the Vadoo AI MCP

Paste the JSON snippet shown on the right into your .vscode/mcp.json. Replace [YOUR_TOKEN_HERE] with your endpoint token from cloud.vinkius.com.
3

Switch to Agent mode

Open Copilot Chat (Cmd+Shift+I / Ctrl+Shift+I) and switch to Agent mode using the dropdown. MCP tools are only available in Agent mode — they do not appear in Edit or Ask modes.
4

Verify the connection

In the Copilot Chat input, type # to list available tools. You should see the Vadoo AI tools listed. Try asking: "List my recent Vadoo AI transactions" and Copilot will invoke them automatically.

.vscode/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 VS Code Copilot

You define it organization-wide in `.vscode/mcp.json` and commit that file to your repository. This makes the MCP Server available instantly for every developer on the team.

Yes, you can use `vadooai_generate_caption`. The agent reads a completed video and outputs structured caption data that integrates directly into your documentation files.

The server manages multiple media creation tools, including generating videos, podcasts, and short clips. It provides a centralized way to use these features within your development environment.

Yes, you can prompt the agent to call `vadooai_check_video_status`. This allows your team's code to reliably check for final media details after an asynchronous job finishes.

The server works with video content, text prompts, and structured metadata derived from the generation process. This ensures all outputs are version-controlled alongside your code.

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