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

Q: How do I install the CoreWeave (AI GPU Cloud) MCP server for Claude Code?

Run the claude mcp add command with the server URL in your terminal. Once added, the tools are available for all your headless automation tasks.

Headless GPU management for Claude Code using CoreWeave MCP tools.

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Connect CoreWeave (AI GPU Cloud) MCP to Claude Code

Create your Vinkius account to connect CoreWeave (AI GPU Cloud) to Claude Code 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 Claude Code

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Headless GPU Orchestration for Claude Code

Integrate `create_cluster` into your CI/CD pipelines to spin up GPU resources on demand. Claude Code executes these commands in the terminal without needing a GUI. It monitors your state using `list_clusters` and `list_deployments` during automated test runs. This allows for fully scripted infrastructure management in your shell scripts.

Terminal-based Resource Scaling for Claude Code

Trigger `update_capacity_claim` via CLI to scale your inference nodes based on incoming load. Claude Code handles the adjustment without interrupting your workflow. It cleans up after your jobs finish by calling `delete_deployment` and `delete_cluster`. You keep your cloud footprint lean and cost-effective through simple terminal commands.

Automated Observability for Claude Code

Pipe the output of `query_metrics` into your monitoring scripts to track performance in real-time. Claude Code provides the logic to interpret these metrics and alert on issues. It also pulls logs with `query_logs` to debug failed deployments during CI runs. You get immediate visibility into your infrastructure status from the command line.

Setup guide

Set up CoreWeave (AI GPU Cloud) MCP in Claude Code

Prerequisites

Claude Code CLI installed (npm install -g @anthropic-ai/claude-code)
Active Vinkius subscription with a valid endpoint token

1

Run the add command

Open your terminal and run the command shown on the right. Replace [YOUR_TOKEN_HERE] with your endpoint token from cloud.vinkius.com. Use --scope user to make it available across all projects.
2

Verify the connection

Start a Claude Code session and type /mcp to list connected servers. You should see coreweave-ai-gpu-cloud-mcp with a green status indicator.
3

Start using tools

Ask Claude Code something like "Check my latest CoreWeave (AI GPU Cloud) transactions." It will automatically discover and invoke the available CoreWeave (AI GPU Cloud) tools.

Terminal

claude mcp add --transport http coreweave-ai-gpu-cloud-mcp https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp

Get your connection token →

Prerequisites

Claude Code CLI installed
Active Vinkius subscription with a valid endpoint token

1

Open the config file

Create or edit .mcp.json in your project root for project-level scope, or ~/.claude.json for user-level scope.
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

Restart Claude Code

Start a new Claude Code session. Type /mcp to confirm the server is connected. The tools will be automatically available in your conversation.

.mcp.json

{
  "mcpServers": {
    "coreweave-ai-gpu-cloud-mcp": {
      "type": "url",
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}

Get your connection token →

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Common questions about CoreWeave (AI GPU Cloud) MCP in Claude Code

Run the `claude mcp add` command with the server URL in your terminal. Once added, the tools are available for all your headless automation tasks.

Yes, it is designed for headless environments like Docker or GitHub Actions. Simply pass your credentials and the server will execute commands as expected.

The server uses a single endpoint token provided by Vinkius, which removes the need to store sensitive API keys locally. Your security is managed by our hardened infrastructure.

Only basic resource metadata is exchanged to perform your requested actions. No private code or environment variables are ever transmitted through the MCP server.

All requests are authenticated and scoped to your specific infrastructure account. We use transient memory for all operations, ensuring no persistence of your resource data occurs on our servers.

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