How to Use the Clarifai (Vision AI) MCP in Windsurf

Q: Can Windsurf chain Clarifai (Vision AI) tools together?

Yes. Cascade will autonomously run listmodels to find an ID, then feed that directly into predictmodel. You just ask it to test an image, and it handles the intermediate steps.

Q: How does Clarifai (Vision AI) expose models to Windsurf?

The server exposes the listmodels tool. Cascade calls this to perform structural extraction of your computer vision parameters, pulling the exact model IDs you need for inference.

Q: What happens when I query datasets?

Your agent uses listdatasets to identify precise physical bounds mapping your data structures. It returns the raw configuration so you can build interfaces around your visual nodes.

Q: Is my image data secure when using this MCP Server?

Vinkius isolates your requests inside a V8 sandbox. When predictmodel sends images or URLs for classification, the ephemeral environment processes the payload and immediately destroys the memory state. Nothing persists after the inference completes.

Give Windsurf computer vision powers to build image classification features without leaving your editor.

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Connect Clarifai (Vision AI) MCP to Windsurf

Create your Vinkius account to connect Clarifai (Vision AI) to Windsurf 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 Windsurf

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Map Clarifai (Vision AI) assets via MCP

Cascade needs to know what it is working with before writing your integration code. Calling `list_apps` tells your agent exactly which environments are available under your current compute limits. It grabs the environment context instantly. Once the app is pinned down, Windsurf fires off `list_models` and `list_workflows` to map out the structural parameters driving your AI features. You do not have to dig through web dashboards to find model IDs because your IDE handles the discovery phase automatically.

Explore training datasets directly

Building a UI for image tagging requires knowing the exact semantic bounds of your data. Cascade uses `list_concepts` to extract the tags explicitly attached to your Clarifai limits. It pulls those strings right into your local variables. If you need to verify where the physical data lives, the `list_datasets` tool maps the data structures resolving those visual nodes. Your agent reads the output and drafts the front-end components to match the dataset schema perfectly.

Run predictions from the MCP Server

Testing computer vision models usually means writing boilerplate API wrappers. Not anymore. Windsurf runs `predict_model` to dispatch an automated validation inference straight to the Clarifai network. The agent parses the evaluated bounding image classifications and shows you the JSON response. You tell Cascade to build a gallery view of the predicted tags, and it writes the React code using real inference data.

Setup guide

Set up Clarifai (Vision AI) MCP in Windsurf

Prerequisites

Windsurf IDE installed (macOS, Windows, or Linux)
Active Vinkius subscription with a valid endpoint token

1

Open MCP configuration

Click the Cascade assistant icon in the sidebar, then click the hammer icon (🔨) at the top of the panel. Select "Configure" to open ~/.codeium/windsurf/mcp_config.json.
2

Add the Clarifai (Vision AI) MCP

Paste the JSON snippet shown on the right into the mcpServers object. Replace [YOUR_TOKEN_HERE] with your endpoint token from cloud.vinkius.com.
3

Refresh MCPs

Go back to the hammer icon (🔨) in Cascade and click "Refresh". Windsurf will detect the new server. No full restart is needed — the connection is hot-reloaded.
4

Verify in Cascade

Start a new Cascade conversation and ask something like "Show my Clarifai (Vision AI) payment history." If connected, Cascade will call the Clarifai (Vision AI) tools directly. You will see a green dot next to the server name in the MCP panel.

mcp_config.json

{
  "mcpServers": {
    "clarifai-vision-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 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 Windsurf

Open the MCP Server UI under Settings, then Cascade. Add the server details to your mcp_config.json and click Refresh. You can also grab it straight from the built-in MCP Marketplace.

Yes. Cascade will autonomously run `list_models` to find an ID, then feed that directly into `predict_model`. You just ask it to test an image, and it handles the intermediate steps.

The server exposes the `list_models` tool. Cascade calls this to perform structural extraction of your computer vision parameters, pulling the exact model IDs you need for inference.

Your agent uses `list_datasets` to identify precise physical bounds mapping your data structures. It returns the raw configuration so you can build interfaces around your visual nodes.

Vinkius isolates your requests inside a V8 sandbox. When `predict_model` sends images or URLs for classification, the ephemeral environment processes the payload and immediately destroys the memory state. Nothing persists after the inference completes.

Use it with your favorite AI tools

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