How to Use the New Relic MCP in Mastra AI

Engineer resilient incident response workflows with Mastra AI, connecting directly to your telemetry via this MCP server.

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Connect New Relic MCP to Mastra AI

Create your Vinkius account to connect New Relic to Mastra AI 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 with Mastra AI

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Build incident workflows in Mastra AI

PagerDuty goes off at 3 AM. Instead of waking up a human, your Mastra workflow catches the webhook and starts investigating. The framework grabs `list_alerts` to see what broke, then uses `get_entity_details` to check the affected service. If the API times out, the built-in exponential backoff just tries again until NerdGraph responds.

Branch logic based on NRQL results

Simple agents panic when queries return unexpected data. A proper workflow engine evaluates the output and decides what to do next based on actual metrics. Your agent fires off a `run_nrql` command to check error rates. If the error rate exceeds your threshold, the workflow branches to fetch `get_apm_summary` for deeper context before pinging the on-call engineer.

Require approval for config changes

You probably do not want an autonomous script modifying your primary monitoring views without oversight. We give you control over exactly what executes. By enabling `requireToolApproval` in your MCPClient configuration, the agent can stage a `get_dashboard` read. A human reviews the intended action, clicks approve, and the workflow continues pulling the `list_dashboards` data.

Setup guide

Set up New Relic MCP in Mastra AI

Prerequisites

Node.js 18+ and a TypeScript project
@mastra/mcp + @mastra/core packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run npm install @mastra/mcp @mastra/core plus your preferred model provider (e.g. @ai-sdk/openai).
2

Configure the MCPClient
Create an MCPClient with your Vinkius endpoint as a URL object. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Discover and inject tools
Call mcpClient.listTools() and spread the result into your agent's tools object. All New Relic tools become native Mastra tools.
4

Run with any model
Swap openai("gpt-4o") for any AI SDK-compatible provider. Call agent.generate() and the agent routes tool calls through MCP automatically.

agent.ts

import { MCPClient } from "@mastra/mcp";
import { Agent } from "@mastra/core/agent";
import { openai } from "@ai-sdk/openai";

const mcpClient = new MCPClient({
  id: "new-relic-mcp-client",
  servers: {
    "new-relic-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

const agent = new Agent({
  name: "New Relic Agent",
  model: openai("gpt-4o"),
  instructions: "You have access to New Relic tools.",
  tools: {
    ...(await mcpClient.listTools()),
  },
});

const result = await agent.generate(
  "List recent New Relic transactions"
);
console.log(result.text);

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Why Choose Vinkius

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place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about New Relic MCP in Mastra AI

Pass your Vinkius endpoint URL into the servers object when instantiating the MCP client. Call listTools() and spread the results into your agent's tool array.

The framework automatically manages retries for you. If a tool hits a rate limit, the backoff mechanism waits and attempts the call again automatically.

The client auto-detects the transport layer natively. You provide the URL, and it negotiates the best connection method for the MCP Server automatically.

You can inspect the step-by-step execution logs in your deployment environment. Every tool call and its corresponding NerdGraph response gets recorded for review.

The system operates under a strict zero-trust model. Your service level indicators and entity metadata traverse an isolated tunnel that closes the second the workflow finishes. No data persists on disk.

Use it with your favorite AI tools

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