New Relic AI (LLM Observability) MCP Server for Mastra AI 10 tools — connect in under 2 minutes
Mastra AI is a TypeScript-native agent framework built for modern web stacks. Connect New Relic AI (LLM Observability) through the Vinkius and Mastra agents discover all tools automatically — type-safe, streaming-ready, and deployable anywhere Node.js runs.
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Vinkius supports streamable HTTP and SSE.
import { Agent } from "@mastra/core/agent";
import { createMCPClient } from "@mastra/mcp";
import { openai } from "@ai-sdk/openai";
async function main() {
// Your Vinkius token — get it at cloud.vinkius.com
const mcpClient = await createMCPClient({
servers: {
"new-relic-ai-llm-observability": {
url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
},
},
});
const tools = await mcpClient.getTools();
const agent = new Agent({
name: "New Relic AI (LLM Observability) Agent",
instructions:
"You help users interact with New Relic AI (LLM Observability) " +
"using 10 tools.",
model: openai("gpt-4o"),
tools,
});
const result = await agent.generate(
"What can I do with New Relic AI (LLM Observability)?"
);
console.log(result.text);
}
main();
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About New Relic AI (LLM Observability) MCP Server
Connect your New Relic AI account to any AI agent and take full control of your LLM observability, token cost tracking, and performance analytics through natural conversation.
Mastra's agent abstraction provides a clean separation between LLM logic and New Relic AI (LLM Observability) tool infrastructure. Connect 10 tools through the Vinkius and use Mastra's built-in workflow engine to chain tool calls with conditional logic, retries, and parallel execution — deployable to any Node.js host in one command.
What you can do
- LLM Telemetry Audit — Retrieve detailed LLM chat completion messages and prompt inputs directly from your agent to understand literal model behavior in real-time
- Token Cost Tracking — Execute structural extraction of model costs to calculate exact USD token consumption across your entire AI infrastructure securely
- Performance Monitoring — Extract p95 latency matrices and average response times to ensure your LLM text generation remains performant and sub-second
- User Feedback Loop — Retrieve chronological feedback messages and 1-5 rating scores dumped by human supervisors to identify quality regressions natively
- Custom NRQL Execution — Run sophisticated read-only queries using the New Relic Query Language (NRQL) to extract rich insights from multi-tenant AI datasets instantly
- Custom Event Injection — Post atomic generic telemetry rows to track internal agent states and custom behavioral markers across your observability pipeline
- Resource Discovery — Enumerate active APM apps, dashboards, and alert policies to audit your AI environment's structural health and PagerDuty configurations
The New Relic AI (LLM Observability) MCP Server exposes 10 tools through the Vinkius. Connect it to Mastra AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect New Relic AI (LLM Observability) to Mastra AI via MCP
Follow these steps to integrate the New Relic AI (LLM Observability) MCP Server with Mastra AI.
Install dependencies
Run npm install @mastra/core @mastra/mcp @ai-sdk/openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.ts and run with npx tsx agent.ts
Explore tools
Mastra discovers 10 tools from New Relic AI (LLM Observability) via MCP
Why Use Mastra AI with the New Relic AI (LLM Observability) MCP Server
Mastra AI provides unique advantages when paired with New Relic AI (LLM Observability) through the Model Context Protocol.
Mastra's agent abstraction provides a clean separation between LLM logic and tool infrastructure — add New Relic AI (LLM Observability) without touching business code
Built-in workflow engine chains MCP tool calls with conditional logic, retries, and parallel execution for complex automation
TypeScript-native: full type inference for every New Relic AI (LLM Observability) tool response with IDE autocomplete and compile-time checks
One-command deployment to any Node.js host — Vercel, Railway, Fly.io, or your own infrastructure
New Relic AI (LLM Observability) + Mastra AI Use Cases
Practical scenarios where Mastra AI combined with the New Relic AI (LLM Observability) MCP Server delivers measurable value.
Automated workflows: build multi-step agents that query New Relic AI (LLM Observability), process results, and trigger downstream actions in a typed pipeline
SaaS integrations: embed New Relic AI (LLM Observability) as a first-class tool in your product's AI features with Mastra's clean agent API
Background jobs: schedule Mastra agents to query New Relic AI (LLM Observability) on a cron and store results in your database automatically
Multi-agent systems: create specialist agents that collaborate using New Relic AI (LLM Observability) tools alongside other MCP servers
New Relic AI (LLM Observability) MCP Tools for Mastra AI (10)
These 10 tools become available when you connect New Relic AI (LLM Observability) to Mastra AI via MCP:
custom_nrql
Note that NRQL is read-only. Irreversibly vaporize explicit validations extracting rich Churn flags
list_alert_policies
Inspect deep internal arrays mitigating specific Plan Math
list_apm_apps
Dispatch an automated validation check routing explicit Gateway history
list_dashboards
Identify precise active arrays spanning native Gateway auth
post_custom_event
/events` inserting absolute generic `CustomAITelemetry` rows tracking internal agent state. Enumerate explicitly attached structured rules exporting active Billing
query_llm_costs
Perform structural extraction of properties driving active Account logic
query_llm_errors
Identify precise active arrays spanning native Hold parsing
query_llm_events
Identify bounded CRM records inside the Headless New Relic Platform
query_llm_feedback
Retrieve explicit Cloud logging tracing explicit Vault limits
query_llm_latency
Provision a highly-available JSON Payload generating hard Customer bindings
Example Prompts for New Relic AI (LLM Observability) in Mastra AI
Ready-to-use prompts you can give your Mastra AI agent to start working with New Relic AI (LLM Observability) immediately.
"Show me the last 5 LLM events for the 'OpenAI' vendor"
"What is my total LLM token cost for the last 24 hours?"
"Run NRQL: SELECT count(*) FROM LlmEvent WHERE duration > 2 SINCE 1 hour ago"
Troubleshooting New Relic AI (LLM Observability) MCP Server with Mastra AI
Common issues when connecting New Relic AI (LLM Observability) to Mastra AI through the Vinkius, and how to resolve them.
createMCPClient not exported
npm install @mastra/mcpNew Relic AI (LLM Observability) + Mastra AI FAQ
Common questions about integrating New Relic AI (LLM Observability) MCP Server with Mastra AI.
How does Mastra AI connect to MCP servers?
MCPClient with the server URL and pass it to your agent. Mastra discovers all tools and makes them available with full TypeScript types.Can Mastra agents use tools from multiple servers?
Does Mastra support workflow orchestration?
Connect New Relic AI (LLM Observability) with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect New Relic AI (LLM Observability) to Mastra AI
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.