How to Use the Gumlet MCP in VS Code Copilot

Q: Can VS Code Copilot run automated tests on our Gumlet video uploads?

Yes, the agent can call createvideoupload during a chat session to generate a test upload link. This helps your team quickly verify that the ingestion endpoints are responding.

Q: Does VS Code Copilot allow us to manage video folders?

Yes, the agent uses createcollection and listvideocollections to organize your media assets. You can manage your folder structure without leaving your coding workspace.

Share automated media workflows across your engineering team in VS Code Copilot.

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Connect Gumlet MCP to VS Code Copilot

Create your Vinkius account to connect Gumlet 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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Commit shared media workflows to VS Code Copilot

Keep your entire engineering team aligned. By checking this MCP server configuration into your git repository, every developer instantly gets access to `list_image_sources` and `list_video_collections` from their chat panel. New developers can query active media directories without hunting down API keys or dashboard invites. It standardizes how your team interacts with the video pipeline.

Validate media delivery pipelines in team chat

Copilot uses `get_video_details` to verify if a video is fully processed or if it was removed using `delete_video`. This instant validation prevents broken links from reaching your staging environment. Developers can check asset status before merging pull requests. This shared MCP workflow ensures no broken media files ever make it to your production branches.

Analyze playback performance in the terminal

The Copilot agent calls `get_video_analytics` to pull real-time stream performance and viewer counts into your editor. This lets your infrastructure team trace playback issues to specific regions or video IDs. You get immediate diagnostic data without switching to an external browser tab. This direct MCP connection keeps your debugging workflow focused inside your workspace.

Setup guide

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

.vscode/mcp.json

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

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Common questions about Gumlet MCP in VS Code Copilot

Save the server settings in your project's workspace configuration file and commit it to your repository. Team members with the required extension will automatically load the tools on startup.

Yes, the agent can call `create_video_upload` during a chat session to generate a test upload link. This helps your team quickly verify that the ingestion endpoints are responding.

Yes, the agent uses `create_collection` and `list_video_collections` to organize your media assets. You can manage your folder structure without leaving your coding workspace.

The server respects your account rate limits. If your team exceeds these limits during heavy testing, the API returns a standard rate-limit error which Copilot displays in the chat.

Your active webhook URLs and team member emails retrieved via `list_webhooks` and `list_org_users` are processed locally. They are never cached or stored on external configuration servers.

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