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Vinkius

New Relic AI (LLM Observability) Connector for AI agents.

10 live capabilities

Monitor LLM token costs and p95 latency metrics in real time.

Live agent request New Relic AI (LLM Observability) / Connector

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Why people use New Relic AI (LLM Observability)

New Relic AI LLM Observability for Tracking Token Costs

With this Connector, you just ask your agent. You can stay in your workspace and ask for the last hour of token costs or check the feedback scores from your human supervisors. It brings the data to you, so you can make decisions based on facts rather than guessing what the dashboard is trying to tell you.

  • Claude
  • ChatGPT
  • Gemini
  • Cursor
  • Visual Studio Code
  • Windsurf

What Vinkius changes

You get a direct line to your New Relic telemetry without leaving your chat window.

Use it from Claude, ChatGPT, Cursor or another AI client you already have.

One account · 5,900+ Connectors

  1. Real-world use case 01

    Checking a sudden spike in costs

    An AI engineer sees a spike in costs and asks the agent to run query_llm_costs to see which model is burning the budget.

  2. Real-world use case 02

    Debugging slow response times

    Users complain about slow responses, so the engineer uses query_llm_latency to find the p95 spikes in specific regions.

  3. Real-world use case 03

    Verifying human satisfaction

    A team wants to see if a new prompt is working.

Complete set · 10capabilities

The complete New Relic AI (LLM Observability) capability set.

These are the exact actions your AI can choose when you ask it to work with New Relic AI (LLM Observability).

Capability set01 / 03

01—04

4 capabilities in this set.

Part of 10 available through New Relic AI (LLM Observability).

  1. 01 Capability

    Query llm feedback

    Retrieve Cloud logging tracing for explicit Vault limits and human ratings. This pulls in your supervisor scores.

  2. 02 Capability

    List alert policies

    Inspect internal arrays that handle specific Plan Math. This helps you see what's mitigating specific logic issues.

  3. 03 Capability

    List apm apps

    Run automated validation checks for explicit Gateway history. It helps you verify the routing of your history.

  4. 04 Capability

    Custom nrql

    Execute read-only queries to extract rich Churn flags from your data. Use this for deep, custom data analysis.

Capability set02 / 03

05—07

3 capabilities in this set.

Part of 10 available through New Relic AI (LLM Observability).

  1. 05 Capability

    List dashboards

    Identify active arrays spanning native Gateway auth. It helps you see which dashboards are currently active.

  2. 06 Capability

    Query llm errors

    Identify active arrays spanning native Hold parsing for error tracking. Use this to find specific failures.

  3. 07 Capability

    Query llm costs

    Extract properties that drive active Account logic for cost tracking. This shows you exactly where the money goes.

Capability set03 / 03

08—10

3 capabilities in this set.

Part of 10 available through New Relic AI (LLM Observability).

  1. 08 Capability

    Query llm events

    Identify bounded CRM records inside the Headless New Relic Platform. This helps you see specific event records.

  2. 09 Capability

    Query llm latency

    Provision a JSON Payload for hard Customer bindings and latency data. Use this to see p95 response times.

  3. 10 Capability

    Post custom event

    Insert CustomAITelemetry rows to track internal agent states and billing rules. This helps you log custom markers.

Set up in minutes

One URL. Then ask New Relic AI (LLM Observability) to work.

Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use New Relic AI (LLM Observability) from the conversation.

Choose your client

Live preview
Advanced clients IDE · CLI

Claude · Web + desktop

Official guide ↗

Connector URL · ready to paste

Streamable HTTP
https://edge.vinkius.com/vk_preview_oqdaAroeFoXBv9yPI4WsHZZZZZuzqhwVoSn1YCyq/mcp
  1. Step 01

    Open Connectors

    In Claude Web or Claude Desktop, open Settings and choose Connectors.

  2. Step 02

    Add the URL

    Choose Add custom connector, name it New Relic AI (LLM Observability), and paste the URL above.

  3. Step 03

    Turn it on in chat

    Select +, open Connectors, and enable New Relic AI (LLM Observability) for the conversation.

Where the request belongs

Work New Relic AI can move forward.

Built around the request

This is for the AI engineer who's tired of hunting through Grafana or New Relic dashboards at 2am just to see why a prompt is failing or why the bill is so high.

01

AI Engineer

Checks model accuracy and prompt performance during a Tuesday sprint without manual dashboard navigation.

02

Observability Lead

Monitors global token costs and p95 latency benchmarks to optimize the company's infrastructure spend.

03

DevOps Engineer

Audits APM app health and verifies alert policy triggers across multiple AI environments.

Build the capability set

Add more capabilities.

Each Connector adds new actions and data without changing how you work.

Browse Connectors
Datadog AI (LLM Observability) logo
01 10 capabilities

Datadog AI (LLM Observability)

Monitor LLM performance via Datadog. track token usage, audit prompts, and monitor AI model metrics directly from any AI agent.

View Connector
Helicone (LLM Observability) logo
02 10 capabilities

Helicone (LLM Observability)

Monitor LLM usage via Helicone. track requests, analyze costs, measure latency, and manage prompts.

View Connector
LangSmith logo
03 3 capabilities

LangSmith

Observability and evaluation platform for LLM applications. monitor traces, debug agent runs, and track performance metrics across your AI stack.

View Connector
Langfuse (LLM Tracing & Evals) logo
04 10 capabilities

Langfuse (LLM Tracing & Evals)

Monitor LLM apps via Langfuse. track traces, manage prompt templates, and audit evaluation scores.

View Connector
LangSmith (LLM Observability & Hub) logo
05 6 capabilities

LangSmith (LLM Observability & Hub)

Monitor LLM apps via LangSmith. track traces, audit prompt templates, and manage evaluation datasets.

View Connector
Portkey logo
06 10 capabilities

Portkey

AI gateway observability: monitor logs, costs, and manage LLM configurations via agents.

View Connector

Bring your own AI

Change the model, client or framework. Keep New Relic AI connected.

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Before you connect

Questions about New Relic AI.

The practical details behind the request, access and result.

Can the New Relic AI MCP help me see how much my AI agents are costing me?

Yes, it pulls your token consumption data directly so you can see the exact USD cost across your entire infrastructure.

How do I check if my LLM responses are getting faster with the New Relic AI MCP?

You can ask your agent to pull p95 latency and average response times to see real-time performance trends.

Can I use the New Relic AI MCP to see what my human supervisors think of the AI?

It retrieves chronological feedback messages and 1-5 rating scores dumped by your human supervisors.

Does the New Relic AI MCP let me run complex queries on my data?

Yes, it allows you to run custom NRQL queries to extract specific insights from your multi-tenant AI datasets.

Can I use the New Relic AI MCP to track custom internal states?

You can post custom telemetry rows to track internal agent states and behavioral markers across your pipeline.

Is the New Relic AI MCP safe for my data?

It connects to your existing New Relic account and follows your established security and permissions.

Can I check my total AI token costs through my agent?

Yes. Use the query_llm_costs capability. Your agent will execute a NRQL aggregation summing the tokenSpanCost property from your LLM events over the last 24 hours, faceted by model, to provide a clear financial breakdown.

How do I monitor the p95 latency of my LLM generations?

The query_llm_latency capability retrieves the average duration and latency matrices for your AI providers. Your agent will report the results as a timesheet or summary, helping you identify performance bottlenecks instantly.

Can my agent run custom NRQL queries against my telemetry data?

Absolutely. Use the custom_nrql capability to provide any valid read-only NRQL string. Your agent will query New Relic's NerdGraph API and return the resulting dataset, allowing for complete flexibility in how you analyze your AI operations.

One connection away

Give your agent a direct line to New Relic AI.

Connect New Relic AI once. Keep it beside 5,900+ managed Connectors when the next task needs more.

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