How to Use the New Relic AI (LLM Observability) MCP in Cline

Q: Can Cline write custom dashboard configurations based on New Relic AI (LLM Observability) data?

Yes, the agent can read your active configurations using listdashboards. It can then write updated configuration files or build custom local dashboards based on that telemetry.

Q: How does Cline handle error auditing with New Relic AI (LLM Observability)?

The agent queries queryllmerrors to find recent issues. It analyzes the stack traces, locates the offending files in your workspace, and writes code to fix the root cause.

Q: Can I post custom events back to my telemetry dashboard?

You can. The agent uses postcustomevent to send custom application metrics straight to your dashboard, making it easy to track custom milestones.

Let Cline write code, run tests, and monitor your production LLM metrics using live telemetry inside VS Code.

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Connect New Relic AI (LLM Observability) MCP to Cline

Create your Vinkius account to connect New Relic AI (LLM Observability) 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 New Relic AI (LLM Observability) with Cline

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Automate telemetry audits with this MCP Server

By calling `query_llm_latency`, Cline checks if your latest code changes made your model responses slower. The agent handles end-to-end tasks by writing code and verifying its impact in production. It retrieves real-time performance data to verify your optimizations. You don't have to leave VS Code to check if your production application is lagging.

Map costs and system errors in Cline

The `query_llm_costs` tool allows your MCP agent to keep track of token usage and financial data. When your budget is on the line, the agent keeps track of token usage. If things go wrong, Cline uses `query_llm_errors` to identify failed API requests. It then writes the necessary code fixes to handle those specific exceptions.

Manage active dashboards and alert policies

Running `list_dashboards` and `list_alert_policies` lets the agent verify that your telemetry views are up to date. Keeping your monitoring setup clean is easy when your agent can inspect your current configurations. The agent can also use `list_apm_apps` to find which services are currently reporting data. This helps you maintain visibility across your entire system.

Setup guide

Set up New Relic AI (LLM Observability) 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 new-relic-ai-llm-observability-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 New Relic AI (LLM Observability) 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": {
    "new-relic-ai-llm-observability-mcp": {
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}

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Common questions about New Relic AI (LLM Observability) MCP in Cline

Open the Cline sidebar and click on the MCP Servers icon. You can add the server via the UI or edit your `cline_mcp_settings.json` file directly with the Vinkius endpoint.

Yes, the agent can read your active configurations using `list_dashboards`. It can then write updated configuration files or build custom local dashboards based on that telemetry.

The agent queries `query_llm_errors` to find recent issues. It analyzes the stack traces, locates the offending files in your workspace, and writes code to fix the root cause.

You can. The agent uses `post_custom_event` to send custom application metrics straight to your dashboard, making it easy to track custom milestones.

Your data is protected. This MCP Server runs inside an ephemeral, zero-trust V8 sandbox that only transfers read-only metrics like token costs and latency values directly to your local VS Code client.

Use it with your favorite AI tools

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

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