How to Use the Dopplio MCP in VS Code Copilot

Share automated Dopplio video and PDF workflows across your entire engineering team using VS Code Copilot.

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Connect Dopplio MCP to VS Code Copilot

Create your Vinkius account to connect Dopplio 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 Dopplio with VS Code Copilot

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Standardize video generation across your dev team

Commit your `.vscode/mcp.json` file to git so every developer gets access to Dopplio's `generate_video` instantly inside VS Code Copilot. This VS Code Copilot MCP setup generates personalized clips without hunting down API keys. VS Code Copilot uses `list_videos` to pull the shared Dopplio team library directly into the chat panel.

Build documents and capture previews in the editor

Generate clean PDF attachments by telling VS Code Copilot to run `render_pdf` on the Dopplio server. The agent handles the backend compilation and hands the download link directly to your VS Code Copilot chat. If you need a visual check, the VS Code Copilot agent triggers `capture_screenshot` to verify the page layout of your Dopplio landing page.

Monitor production render queues with this MCP Server

Active rendering jobs are tracked when VS Code Copilot calls `get_render_status` to alert you to any bottlenecks in your Dopplio delivery pipeline. When troubleshooting a specific customer issue, the VS Code Copilot agent runs `get_video_details` to inspect the metadata and payload configuration of that exact Dopplio render.

Setup guide

Set up Dopplio 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 Dopplio 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 Dopplio tools listed. Try asking: "List my recent Dopplio transactions" and Copilot will invoke them automatically.

.vscode/mcp.json

{
  "mcpServers": {
    "dopplio-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 Dopplio. 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 Dopplio MCP in VS Code Copilot

Create a .vscode/mcp.json file in your repository root and add the Dopplio MCP server settings. Once committed, any team member using VS Code Copilot can access tools like generate_video and render_pdf.

Yes, you can highlight a JSON array of customer data in VS Code Copilot and ask it to run generate_video for each record. The agent will process the batch through Dopplio and report back.

Simply ask VS Code Copilot to inspect a video ID. The agent will execute get_video_details to return the full Dopplio payload structure, including variables and render times, right in your editor.

Preview design changes instantly without leaving VS Code Copilot by letting the agent read your active HTML file in the editor and pass it to render_pdf on the Dopplio server.

All Dopplio video assets and personalization variables processed through VS Code Copilot are encrypted in transit. Your team's API tokens are stored securely in VS Code's native credential store, never exposed in plaintext.

Use it with your favorite AI tools

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