How to Use the Anyscale MCP in Cline

Q: How does Cline interact with Anyscale cluster services?

Cline calls listservices to inspect your active endpoints via this MCP Server. It uses this information to write and test backend integration code without manual API checks.

Q: Can Cline trigger text generation using my Anyscale models?

Yes. Cline uses the chatcompletion and textcompletion tools to send prompts directly to your hosted LLM endpoints.

Q: What tools does this server provide for checking endpoint status?

It exposes listservices and getservice to check your active deployments. Your agent uses these to verify that your cluster is running before executing API calls.

Let Cline manage your Anyscale deployments and run LLM tests directly inside VS Code.

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Connect Anyscale MCP to Cline

Create your Vinkius account to connect Anyscale to Cline 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 Anyscale with Cline

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Deploy and check endpoints with this MCP Server

The `list_services` tool retrieves the list of all active deployments running on your cluster. Cline uses this MCP integration to verify endpoint availability before writing client-side integration code. If a specific endpoint behaves unexpectedly, the `get_service` tool provides detailed configuration data for that service. Cline inspects these details to troubleshoot connection errors and adjust your API headers.

Generate embeddings and text directly inside Cline

The `generate_embeddings` tool produces semantic vector representations for any text input you feed it. Cline uses this to verify your vector database pipeline by testing real outputs against your local test suites. For raw text generation, the `text_completion` tool processes instruct prompts directly through your hosted endpoints. Cline runs these queries to draft documentation or generate mock data based on live model outputs.

Track cluster training runs autonomously

The `list_jobs` tool fetches active and completed batch training runs from your cluster. Cline reads this list to determine if your custom model training has completed successfully. Once the job is done, the `list_models` tool lists all available endpoints to find your newly trained model ID. Cline then updates your environment variables with the fresh model identifier.

Setup guide

Set up Anyscale MCP in Cline

Prerequisites

VS Code with Cline extension installed
Active Vinkius subscription with a valid endpoint token

1

Open Cline MCP settings

Click the Cline icon in the VS Code sidebar to open the Cline panel. Then click the MCP Servers icon (server stack) at the top-right corner of the panel.
2

Add a remote server

Click "Remote Servers" at the top, then click "Add Remote MCP". In the Name field, type anyscale-mcp. In the URL field, paste your Vinkius endpoint: https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp. Get your token from cloud.vinkius.com.
3

Enable the server

After saving, the server appears in the Cline MCP panel. Toggle the switch to enable it. The status indicator turns green when the connection is live.
4

Start using tools

Return to the Cline chat and ask: "Check my latest Anyscale refund status." Cline will discover the available tools and request your approval before invoking each one — giving you full control over every action.

Cline MCP Settings

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

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Common questions about Anyscale MCP in Cline

Cline calls `list_services` to inspect your active endpoints via this MCP Server. It uses this information to write and test backend integration code without manual API checks.

Yes. Cline uses the `chat_completion` and `text_completion` tools to send prompts directly to your hosted LLM endpoints.

Click the MCP Servers icon in the Cline sidebar and add the server via the Remote Servers tab. Alternatively, you can write the configuration directly into your local `cline_mcp_settings.json` file.

It exposes `list_services` and `get_service` to check your active deployments. Your agent uses these to verify that your cluster is running before executing API calls.

All API keys and prompt texts are handled inside an ephemeral, zero-trust sandbox. Your vector payloads and job configurations are sent directly to your endpoint without persistent caching on intermediate servers.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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