"Prometheus" matching MCP servers:

A proof-of-concept Prometheus MCP server, which likely enables Claude AI to interact with Prometheus monitoring systems through the Model Context Protocol.

An MCP server for Prometheus-based monitoring that enables users to query system metrics, resource usage, and PostgreSQL health across multiple environments. It supports both predefined diagnostic checks and custom PromQL execution for comprehensive server monitoring and troubleshooting.

MCP server for Prometheus metrics and observability. Give Claude (or any MCP-capable agent) read access to your Prometheus instance — query metrics with PromQL, inspect active alerts, and explore scrape targets without leaving the conversation. Tools: prometheus_list_metrics, prometheus_query, prometheus_query_range, prometheus_list_alerts, prometheus_list_targets.

Provides access to Prometheus metrics and queries through standardized Model Context Protocol interfaces, allowing AI assistants to execute PromQL queries and analyze metrics data.

Executes constrained, read-only Prometheus queries for instant metrics, active alerts, and target health, with bounded resource usage and audit records.

Provides access to Prometheus metrics and queries, allowing AI assistants to execute PromQL queries and analyze metrics data through standardized MCP interfaces.

A tool that enables access to Prometheus metrics data through a Model Context Protocol server, allowing interaction with monitoring data using natural language.

A tool that lets users access Prometheus metrics data through a Model Context Protocol server, supporting authentication options for secure data retrieval.

MCP server that enables AI assistants to query and analyze Prometheus metrics through PromQL, with support for metric discovery and authentication.

An MCP server that enables Large Language Models to retrieve, analyze, and query metric data from Prometheus databases through pre-defined routes.

Enables AI assistants to execute PromQL queries and discover metrics across multiple Prometheus tenants using the Model Context Protocol. It supports single and multi-tenant configurations with secure authentication for instant and range query analysis.

Enables querying real-time and historical server performance metrics (CPU, memory, disk IO, load, TCP) from Prometheus via Node Exporter.

Enables access to Amazon Managed Prometheus workspaces through natural language queries. Supports listing workspaces, executing PromQL queries, and retrieving workspace details and metrics with AWS authentication.

Enables natural language Kubernetes cluster operations, SLO monitoring, and PromQL queries via Claude using the Model Context Protocol.

MCP server that enables AI assistants to query Grafana/Loki logs and Thanos/Prometheus metrics directly from MCP-compatible clients like Cursor or Claude Desktop.

Enables assistants to read-only explore and analyze Grafana dashboards and data sources, execute queries against Prometheus and Azure Log Analytics, and run guided investigation workflows.

Enables diagnostics and troubleshooting of OpenShift clusters through storage analysis, resource monitoring, GPU utilization tracking, and pod health checks using Prometheus metrics and the oc CLI.

Gives AI assistants read-only access to a Kubernetes cluster's observability stack — Loki, Prometheus, Tempo, the Kubernetes API — plus AWS telemetry from CloudTrail, Config, ECR, and RDS. 23 tools for querying logs, metrics, traces, Kubernetes events, deployments, and audit history in plain language.

Enables AI agents to query Prometheus metrics and Loki logs for intelligent alert investigation and troubleshooting. Provides service discovery, metric querying, log searching, and correlation tools to help identify root causes of issues.

Governed Prometheus + Grafana operations — firing-alert and scrape-target RCA, alert noise/flapping analysis, silences, and dashboards, with unbypassable audit logging (MCP + CLI), budget/runaway guards, dry-run, and undo/rollback.