New Relic vs Grafana
New Relic and Grafana are two of the most widely used observability platforms, and both ship official MCP servers that let an agent investigate production the way an on-call engineer would. They overlap on the core promise — query your telemetry, read dashboards, and triage incidents through tool calls — but they reflect very different platform philosophies. New Relic is an all-in-one, single-vendor observability cloud, and its server centers on NRQL: agents translate natural language to NRQL, execute it against NRDB, and get metrics, traces, and logs with analysis layered on top, plus entity discovery, alerts, incidents, and rich performance analytics like golden-metric and transaction analysis. Grafana is the open visualization-and-query layer over many backends, and its server reflects that: it queries Prometheus (PromQL), Loki (LogQL), ClickHouse, InfluxDB, CloudWatch, Athena, Snowflake and more through your configured datasources, reads and edits dashboards, renders panels as images, and drives Incident, OnCall, and Sift. Here is how they compare when an agent is the operator.
How they compare
| Dimension | New Relic | Grafana |
|---|---|---|
| Platform model | All-in-one, single-vendor observability cloud — your telemetry lives in NRDB and the agent queries it directly. | Open query/visualization layer over many backends — the agent reaches Prometheus, Loki, ClickHouse, CloudWatch, and more through Grafana datasources. |
| Query language | NRQL is the center of gravity, with a natural_language_to_nrql_query tool plus execute_nrql_query so the model writes and runs queries against NRDB. | Native per-datasource languages — query_prometheus (PromQL), query_loki_logs (LogQL), plus ClickHouse, InfluxDB, CloudWatch, Athena, Snowflake, and Elasticsearch queries. |
| Analysis depth | Rich built-in analytics — analyze_golden_metrics, analyze_transactions, analyze_deployment_impact, error groups, and user-impact/alert-insight reports. | Sift investigations for automated root-cause (find_error_pattern_logs, find_slow_requests) plus Pyroscope profiling and Asserts assertions. |
| Dashboards and incidents | Read dashboards and entities, list alert policies/conditions and recent issues, and search incidents — an investigation-and-triage surface. | Search, read, and edit dashboards, render panels as PNGs, and drive Grafana Incident, OnCall schedules/shifts, and alert rules/routing. |
| Best-fit task | Teams standardized on New Relic who want natural-language NRQL and deep, opinionated performance analytics in one place. | Teams with a multi-backend stack who want one agent to query everything through Grafana and manage dashboards, on-call, and incidents. |
Verdict
Choose New Relic's server when your telemetry already lives in New Relic and you want the agent to lean on NRQL — including natural-language-to-NRQL — plus deep, single-vendor analytics like golden metrics, transactions, and deployment-impact reports. Choose Grafana's server when your observability is spread across Prometheus, Loki, ClickHouse, CloudWatch and friends, and you want one agent to query all of them through your datasources while managing dashboards, OnCall, and incidents. The decision is the classic single-vendor-platform (New Relic) versus open-multi-backend-hub (Grafana) choice — pick the one that matches where your data already lives and how you prefer to query it.
FAQ
- Can the agent write queries for me?
- Yes on both, differently. New Relic offers natural_language_to_nrql_query so the model drafts NRQL from plain English. Grafana exposes per-datasource query tools and query examples, so the agent writes PromQL, LogQL, or SQL against the right backend.
- Which one manages on-call and incidents?
- Grafana drives Grafana OnCall schedules/shifts and Grafana Incident directly. New Relic focuses on searching incidents and managing alert policies and conditions, with reporting on issues and user impact.