"Hearth" matching MCP servers:

MCP server for AI agent deployment health — gateway status, CPU/memory/swap, recent errors from journalctl/dmesg, skill registry integrity, upgrade outcomes, cron + disk usage. Each component gets HEALTHY/DEGRADED/CRITICAL classification with overall rollup.

MCP server for monitoring health of MCP servers, GitHub Actions, GitLab pipelines, and HTTP endpoints with health history, TLS expiry, assertions, diagnostics, and alerts.

A professional-grade MCP server that enables AI assistants to monitor web services, APIs, and HTTP endpoints with enterprise-level security.

MCP server for On-Call Health burnout analysis. Connects AI assistants to your on-call data for workload insights.

Monitors API endpoint health by checking availability, measuring response times, and providing detailed status reports with error handling and timeout protection for the localhost:8080/api/ticket endpoint.

MCP-native health monitoring that probes MCP servers using the list_tools protocol handshake, detects version drift, stores history in SQLite, and generates an HTML dashboard.

Health Check AI - MCP server providing AI-powered tools and automation by MEOK AI Labs

An AI-powered Power BI dataset health monitor that connects Claude to a simulated Power BI tenant for running health checks, diagnosing failures, and prioritizing fixes.

Read-only MCP server providing Microsoft 365 service health status and known incident/outage information from Microsoft Graph. Enables quick answers to whether an issue is a widespread Microsoft outage or specific to a tenant.

An AI agent system that monitors manufacturing equipment health using the Model Context Protocol (MCP). Enables answering natural language questions about equipment status, maintenance, and anomalies through MCP tools.

Provides MCP tools to perform Looker health checks (health_pulse, health_analyze, health_vacuum) via the MCP Toolbox connector.

Enables autonomous infrastructure health management by exposing tools for retrieving system logs, querying a knowledge base, executing SQL analytics, and simulating system commands, all integrated into an AI-driven incident response workflow.

Enables LLMs to monitor server health through natural language, including HTTP endpoint checks, disk/memory/CPU usage, port status, and process listings.

Integrity monitor for MCP server ecosystems, providing real-time health checks, drift detection, and cascade impact analysis for any AI agent.