A
license-
qualityF
maintenanceMulti-machine system monitor with a built-in MCP server that enables AI agents to query health metrics, manage processes, schedule cron jobs, and run diagnostics across local and remote machines.
133
Apache 2.0
74,171 servers. Updated
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"Monitor GitLab notifications and respond to mentions" matching MCP servers:
- AlicenseAqualityBmaintenanceAn MCP server that provides monitoring tools for Codex agents, allowing them to create and wait on conditions using commands, log files, file events, and custom probes, replacing polling loops with event-driven blocking.5264MIT
- AlicenseAqualityAmaintenanceFastMCP server with read-only tools to monitor Redis — queue depths, Celery queue status, connected clients, server/memory info, and per-database key counts53MIT
- AlicenseAqualityBmaintenanceProvides system monitoring tools for VPS including CPU, memory, disk, network ping, top processes, and Docker status, with read-only architecture and security features.4MIT
- AlicenseAqualityBmaintenanceMCP server for monitoring health of MCP servers, GitHub Actions, GitLab pipelines, and HTTP endpoints with health history, TLS expiry, assertions, diagnostics, and alerts.22882MIT
- Alicense-qualityAmaintenancePlug-and-play homelab dashboard in one container — GPU, local-AI VRAM, Docker, systemd, host health. Built-in read-only MCP server so AI agents can explore it too.181MIT
- Alicense-qualityBmaintenanceProvides read-only monitoring of Apache Airflow DAGs, including listing active DAGs, fetching recent runs, and analyzing execution history and performance metrics.1MIT
- Alicense-qualityBmaintenanceMCP server that analyzes AI agent execution logs to calculate reliability scores, detect failure patterns, and suggest concrete improvements for making AI agents more reliable.MIT
- Flicense-qualityAmaintenanceProvides real-time monitoring of AI agents, context, usage limits, workflows, files, Git, tests, builds, errors, secrets, and model-economy advice for tools like Claude Code, Codex, and Cursor, with 30 MCP tools for comprehensive observability.1
- Flicense-qualityBmaintenanceServer Monitor MCP is a Linux server inspection service with web backend and MCP interface. It allows you to manage SSH hosts and query server metrics via natural language.
- Flicense-qualityDmaintenanceEnables Claude to monitor CPU, memory, disk, processes, network connections, Docker containers, and system logs for system diagnostics and troubleshooting.
- Flicense-qualityBmaintenanceMCP server that lets AI coding agents report task progress and milestones, providing a real-time web dashboard and macOS notifications for monitoring multiple AI workbenches.
- Flicense-qualityDmaintenanceMonitors ML models in production for data drift and performance degradation, providing automated alerts and retraining recommendations.
- Flicense-qualityBmaintenanceRead-only MCP server for monitoring Make.com scenario errors from ChatGPT, enabling listing scenarios, viewing recent errors, and getting execution details.
- AlicenseAqualityDmaintenanceIdentifies resource-intensive processes on macOS across CPU, memory, and network usage, with tools for detailed process filtering and system overview.323MIT
- Alicense-qualityCmaintenanceMCP-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.43MIT
- Alicense-qualityCmaintenanceSLA observation broker for the A2A network: agents register public health endpoints with target uptime and latency, and the shim probes them to record breaches.MIT
- Flicense-qualityDmaintenancePaid remote MCP server for monitoring AI agent runs, detecting failures, replaying tool-call incidents, issuing SLA receipts, and exporting client status.
- Flicense-qualityDmaintenanceGives AI agents real-time access to system metrics, process management, and container orchestration.
- Flicense-qualityCmaintenanceMCP server that filters Kubernetes warning/failure events and presents them to AI assistants for diagnostics. Enables AI to identify and troubleshoot cluster issues without consuming context on normal events.