How to Use the Clarifai (Vision AI) MCP in VS Code Copilot

Equip your engineering team with Clarifai (Vision AI) capabilities directly inside VS Code Copilot using a shared MCP Server.

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Connect Clarifai (Vision AI) MCP to VS Code Copilot

Create your Vinkius account to connect Clarifai (Vision 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 Clarifai (Vision AI) with VS Code Copilot

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Validate vision pipelines across your team

`list_workflows` inspects the exact chaining of your active computer vision pipelines. Copilot reads these structures to ensure your local backend code matches the deployed cloud architecture. `list_apps` tracks global compute limits across your workspace. Your team avoids hitting usage caps during collaborative testing phases.

Run predictions inside VS Code Copilot

`predict_model` executes image classification tasks directly from the chat pane. Copilot uses the return payload to suggest precise code for handling bounding boxes. Developers do not need to leave the editor to test endpoint responses. The MCP server feeds real data directly to your active coding session.

Audit dataset bounds and active models

`list_datasets` identifies the exact physical bounds of your training datasets. Copilot references these structures when writing scripts to process visual files. `list_models` and `list_concepts` fetch the active parameters and semantic tags. This gives your agent the context needed to write accurate vision-processing code.

Setup guide

Set up Clarifai (Vision 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 Clarifai (Vision 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 Clarifai (Vision AI) tools listed. Try asking: "List my recent Clarifai (Vision AI) transactions" and Copilot will invoke them automatically.

.vscode/mcp.json

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

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Clarifai. 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 Clarifai (Vision AI) MCP in VS Code Copilot

Create a .vscode/mcp.json file in your repository root and commit it. Every developer on your team will automatically get access to the vision tools.

Yes. When you ask Copilot to analyze an image, it triggers the prediction tool. The results are formatted and displayed directly in your chat sidebar.

No. By committing the configuration file, your entire team inherits the setup. Copilot handles the tool connections in the background.

You need VS Code version 1.96 or higher. Make sure your Copilot extension is updated and switched to Agent mode.

All visual payloads are sent directly to Clarifai over encrypted HTTPS. The MCP server runs in a secure, ephemeral V8 isolate that processes data in memory without saving it to disk.

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