"Prometheus" matching MCP servers:

Provides seamless integration between AI assistants and Prometheus, enabling natural language interactions with your monitoring infrastructure. This server allows for effortless querying, discovery, and analysis of metrics.

Prometheus-MCP is an AI Creative Director MCP server that enhances creative output from models like Claude and GPT to expert-level quality through iterative improvement loops.

Enables agents to distill web pages into facts with citations, remember and recall project memory, and manage API keys and usage via MCP tools.

A Model Context Protocol server that enables AI assistants to query Prometheus metrics, discover available data, and analyze system performance through natural language interactions.

Enables interaction with Prometheus Alertmanager to retrieve, filter, and manage alerts and silences through natural language commands in Claude AI.

Unified observability gateway for AI agents — one MCP server for Prometheus, Loki, and any backend.

Enables AI assistants to query Grafana datasources (Prometheus/Loki metrics and SQL databases like ClickHouse/Postgres/MySQL) and search or inspect dashboards through natural language, using read-only access to Grafana's API.

Enables agents to explore and operate Grafana by searching and reading dashboards and folders, querying datasources such as Prometheus, Loki and SQL, and inspecting alert rules and annotations. Its safe-by-default access modes gate dashboard and folder creation, editing and deletion behind escalating permission levels.

A comprehensive Model Context Protocol (MCP) server for Grafana, Prometheus, Kafka UI, and Datadog. Features a secure "Bring Your Own Key" (BYOK) architecture where credentials stay local. Provides tools for metrics querying, dashboard inspection, Kafka lag monitoring, and unified health checks.

An MCP server that enables Claude to manage infrastructure across Kubernetes, Docker, Prometheus, and Terraform through natural language. It provides over 42 specialized tools with a safety-first design, including risk-based command classification and audit logging.

Enables AI assistants to interact with Grafana dashboards, datasources, alerts, incidents, and monitoring data through 43 comprehensive tools. Supports querying Prometheus metrics, Loki logs, managing incidents, and dashboard operations with full authentication support.

Unified MCP server for DevOps engineers that provides real-time read and write access to Kubernetes, ArgoCD, Prometheus, and PagerDuty from any MCP-compatible AI agent.

Enables AI-powered integration with Grafana instances through 52 MCP tools for dashboard management, Prometheus/Loki queries, alerting, and administrative functions. Supports complete Grafana functionality including metrics exploration, log analysis, and incident response through natural language.

Enables Claude AI to interact with Prometheus Alertmanager for alert retrieval, silence management, and alert grouping through natural language.

Enables AI agents to read Grafana dashboards, alert rules, and query datasources (Prometheus, Loki, etc.) through MCP tools, integrating Grafana monitoring into the IDE.

A local TypeScript MCP gateway that unifies SSH, Prometheus, and MySQL tools under a single loopback HTTP service, featuring a web console for configuration and health monitoring.

Enables incident responders to query and correlate observability and DevOps evidence across Grafana, Prometheus, Loki, Uptime Kuma, CloudWatch, IAM, and PostHog from a local MCP client, with bounded reads and redacted audit records.

Gives AI coding agents read-only access to Grafana's Loki logs, Prometheus metrics, Tempo traces and active alerts from within a project, using per-project context declared in the repo and one-command switching between test and prod environments. Credentials are discovered by parsing shell rc files directly, so it works even when spawned as a non-interactive MCP client process.

Enables LLM agents to discover and invoke guarded web search, read-only SQLite queries, and sandboxed file read/write tools over the Model Context Protocol. It adds schema validation, rate limiting, output sanitization, request-ID logging, and Prometheus metrics at the protocol boundary.

Enables MCP-capable harnesses to apply TypeSafe/Jev's System One decision model through judgment primitives and task-shaped tools, with local event logging and Prometheus metrics for impact tracking.