How to Use the New Relic AI (LLM Observability) MCP in Mastra AI
Add deep observability to your Mastra AI workflows with New Relic AI (LLM Observability) for precise monitoring.
Works with every AI agent you already use
…and any MCP-compatible client
Connect New Relic AI (LLM Observability) MCP to Mastra AI
Create your Vinkius account to connect New Relic AI (LLM Observability) 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.
Workflow-aware telemetry for Mastra AI
Integrate `query_llm_costs` and `query_llm_latency` into your Mastra agents to monitor resource consumption during complex chains. It ensures your workflows stay within budget and performance targets. When a workflow branches, you can verify the performance impact of each path. It provides the data points needed for automated retry logic.
Automated error recovery and auditing
Use `query_llm_errors` to trigger conditional branching in your agents when performance degrades. If the tool detects a spike in errors, your workflow can automatically route to a secondary model or human oversight. This setup turns observability into an active part of your agent's decision-making process. You prevent downtime by acting on real-time health data.
Centralized event reporting
The `post_custom_event` tool lets your agents report their internal state back to your observability platform. It records every transition in your multi-step workflows. This creates a full audit trail for every agent run. You see exactly where a workflow stalled or which step consumed the most tokens.
Set up New Relic AI (LLM Observability) MCP in Mastra AI
Prerequisites
- Node.js 18+ and a TypeScript project
-
@mastra/mcp+@mastra/corepackages - Active Vinkius subscription with a valid endpoint token
- 1
Install dependencies
Run
npm install @mastra/mcp @mastra/coreplus your preferred model provider (e.g.@ai-sdk/openai). - 2
Configure the MCPClient
Create an
MCPClientwith your Vinkius endpoint as aURLobject. 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'stoolsobject. All New Relic AI (LLM Observability) tools become native Mastra tools. - 4
Run with any model
Swap
openai("gpt-4o")for any AI SDK-compatible provider. Callagent.generate()and the agent routes tool calls through MCP automatically.
import { MCPClient } from "@mastra/mcp";
import { Agent } from "@mastra/core/agent";
import { openai } from "@ai-sdk/openai";
const mcpClient = new MCPClient({
id: "new-relic-ai-llm-observability-mcp-client",
servers: {
"new-relic-ai-llm-observability-mcp": {
url: new URL(
"https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
),
},
},
});
const agent = new Agent({
name: "New Relic AI (LLM Observability) Agent",
model: openai("gpt-4o"),
instructions: "You have access to New Relic AI (LLM Observability) tools.",
tools: {
...(await mcpClient.listTools()),
},
});
const result = await agent.generate(
"List recent New Relic AI (LLM Observability) transactions"
);
console.log(result.text); Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by New Relic AI. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
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60%
lower AI costs
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Common questions about New Relic AI (LLM Observability) MCP in Mastra AI
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