How to Use the CoreWeave (AI GPU Cloud) MCP in Windsurf

Q: How do I link CoreWeave (AI GPU Cloud) with Windsurf?

Add the server details to your mcpconfig.json file inside the Windsurf settings. Once refreshed, Cascade detects the available tools and begins interacting with your GPU resources.

Q: What happens to my logs when using CoreWeave (AI GPU Cloud) in Windsurf?

Logs are fetched on-demand through the querylogs tool. No persistent data storage occurs on the client side, keeping your operational history isolated.

Provision GPU clusters and manage inference gateways directly in Windsurf using autonomous Cascade agents.

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Connect CoreWeave (AI GPU Cloud) MCP to Windsurf

Create your Vinkius account to connect CoreWeave (AI GPU Cloud) 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 CoreWeave (AI GPU Cloud) with Windsurf

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Full Infrastructure Control for Windsurf

Cascade reads your infrastructure goals and triggers `create_cluster` or `create_deployment` without manual intervention. You get a live view of your cloud resources while the agent handles the heavy lifting. It manages networking segments through `create_vpc` and `delete_vpc` as part of its planning cycle. You define the architecture and watch Cascade execute the multi-step deployment sequence.

Real-time GPU Monitoring in Windsurf

Run `query_metrics` to pull live utilization stats directly into your IDE context. Cascade interprets these numbers to decide if you need to scale your capacity claims. When anomalies surface, the agent uses `query_logs` to isolate issues within your inference gateways. It saves you from digging through dashboards by surfacing the exact errors inside your editor.

Dynamic Inference Scaling for Windsurf

Adjust your footprint on the fly by calling `update_deployment` or `update_capacity_claim` through the Windsurf interface. The agent keeps your environment synced with your current project requirements. Delete unused assets with `delete_cluster` or `delete_gateway` to keep your environment clean. Cascade handles the cleanup tasks automatically as you complete your dev cycles.

Setup guide

Set up CoreWeave (AI GPU Cloud) 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 CoreWeave (AI GPU Cloud) 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 CoreWeave (AI GPU Cloud) payment history." If connected, Cascade will call the CoreWeave (AI GPU Cloud) tools directly. You will see a green dot next to the server name in the MCP panel.

mcp_config.json

{
  "mcpServers": {
    "coreweave-ai-gpu-cloud-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 CoreWeave. 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 CoreWeave (AI GPU Cloud) MCP in Windsurf

Add the server details to your `mcp_config.json` file inside the Windsurf settings. Once refreshed, Cascade detects the available tools and begins interacting with your GPU resources.

Yes, Cascade handles the full lifecycle of your deployments. It creates, monitors, and updates your inference endpoints using the provided toolset.

Vinkius manages all authentication via unique endpoint tokens. Your credentials never leave the secure V8 sandbox, ensuring your infrastructure access remains private.

Logs are fetched on-demand through the `query_logs` tool. No persistent data storage occurs on the client side, keeping your operational history isolated.

This server only processes infrastructure metadata like cluster IDs and deployment configurations. Your proprietary model weights and sensitive training datasets remain entirely outside this connection.

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