Query metrics with Prometheus

Use the Grafana MCP server so your AI assistant can run PromQL queries against a Prometheus datasource in Grafana. You can run instant or range queries and discover metric and label names and values.

What you’ll achieve

You ask your assistant to check a metric or run a PromQL expression; the assistant uses the server’s Prometheus tools to run the query and return results (or describe available metrics and labels).

Before you begin

The server set up and configured with access to Grafana.
A Prometheus datasource configured in Grafana. The service account must have datasources:query and scope for that datasource (for example, datasources:uid:<uid>).

Run a PromQL query

In your MCP client, ask the assistant to query Prometheus. For example, you might say “What is the current value of up for the Prometheus datasource?” or “Run this PromQL: rate(http_requests_total[5m]).” The assistant uses the server’s Prometheus query tool with the datasource UID and your time range. You can request instant queries (single value) or range queries (series over time).

Discover metrics and labels

Ask the assistant to list metric names, label names, or label values for a given selector. The server exposes tools that call the Prometheus API (metric metadata, label names, label values). Use these to explore what’s available before writing PromQL.

list_prometheus_metric_names defaults to 10 results per page. The product of page and limit must not exceed 10,000. If it does and you need to explore > 10,000 results, narrow the regex to get fewer results. For Prometheus-compatible backends, regex filtering and the fetch limit are sent to the datasource, which must support the limit parameter to bound the response. Cloud Monitoring continues to filter metric descriptors locally.