How to Use the Kling AI (Generative Video & Image) MCP in VS Code Copilot

Q: How do we share Kling AI (Generative Video & Image) across our team in VS Code Copilot?

Create a .vscode/mcp.json file in your repository root and commit it. Every team member with VS Code 1.96+ and Copilot Chat will instantly have access to these MCP tools.

Q: Can VS Code Copilot poll Kling AI (Generative Video & Image) tasks in the background?

Yes, Copilot uses getvideotask or gettryontask to check the status of your active jobs. It runs these checks in the chat thread and alerts you when the assets are ready.

Q: How does the Kling AI (Generative Video & Image) MCP Server display task lists in VS Code Copilot?

Ask Copilot to run listvideotasks to see your queue. It returns a list of recent video generation tasks along with their current status and IDs.

Q: How do I convert a static image to video using this setup?

Use the imagetovideo tool by passing the image URL to the Copilot agent. The agent starts the animation task and tracks it until the final MP4 is ready.

Run Kling AI video and try-on tools directly inside VS Code Copilot with this custom MCP Server.

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Connect Kling AI (Generative Video & Image) MCP to VS Code Copilot

Create your Vinkius account to connect Kling AI (Generative Video & Image) 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 Kling AI (Generative Video & Image) with VS Code Copilot

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Generate cinematic video using this shared MCP Server

The `text_to_video` tool gives your entire engineering team the ability to generate cinematic video assets from text prompts. By committing the server configuration to your repository, everyone on the team can trigger renders. The Copilot agent handles the asynchronous polling by calling `get_video_task` until the MP4 is ready. This keeps your team focused on building the application instead of managing API keys.

Synchronize audio and video inside VS Code Copilot

The `lip_sync_video` tool drives realistic mouth movements on video portraits to match your audio files. Your team can prototype interactive video characters directly from the Copilot chat window. The agent monitors the progress of the synchronization using `get_lipsync_task`. Once the process succeeds, you receive the final MP4 URL to embed in your prototype.

Build apparel try-on pipelines inside VS Code Copilot

The `virtual_try_on` tool merges garment images with model photos to create high-quality product displays. Developers can write and debug try-on logic using live API calls managed by the Copilot agent. The agent calls `get_tryon_task` to fetch the finished composite image. This allows you to verify your application's handling of the final image URLs before deploying to production.

Setup guide

Set up Kling AI (Generative Video & Image) 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 Kling AI (Generative Video & Image) 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 Kling AI (Generative Video & Image) tools listed. Try asking: "List my recent Kling AI (Generative Video & Image) transactions" and Copilot will invoke them automatically.

.vscode/mcp.json

{
  "mcpServers": {
    "kling-ai-generative-video-image-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 Kling 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 Kling AI (Generative Video & Image) MCP in VS Code Copilot

Create a `.vscode/mcp.json` file in your repository root and commit it. Every team member with VS Code 1.96+ and Copilot Chat will instantly have access to these MCP tools.

Yes, Copilot uses `get_video_task` or `get_tryon_task` to check the status of your active jobs. It runs these checks in the chat thread and alerts you when the assets are ready.

Ask Copilot to run `list_video_tasks` to see your queue. It returns a list of recent video generation tasks along with their current status and IDs.

Use the `image_to_video` tool by passing the image URL to the Copilot agent. The agent starts the animation task and tracks it until the final MP4 is ready.

Yes, all garment images, model photos, and task IDs are transmitted over encrypted TLS connections. Vinkius executes the server in an ephemeral sandbox, meaning no files or credentials are ever saved to disk.

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