"Monitor GitLab notifications and respond to mentions" matching MCP servers:

Multi-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.

An 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.

Enables AI clients to create and configure monitors, subscribe to their evidence streams with durable cursors, and process observations with guaranteed at-least-once delivery.

Plug-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.

Enables Claude to monitor CPU, memory, disk, processes, network connections, Docker containers, and system logs for system diagnostics and troubleshooting.

FastMCP server with read-only tools to monitor Redis — queue depths, Celery queue status, connected clients, server/memory info, and per-database key counts

Provides system monitoring tools for VPS including CPU, memory, disk, network ping, top processes, and Docker status, with read-only architecture and security features.

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

Enables MCP-compatible AI assistants to inspect and manage local or remote servers in plain language, covering system health, Docker containers, services, ports, disks, scoped files, and read-only database queries over key-only SSH. Write actions such as container restarts, file edits, and allowlisted dev commands require client approval.

Enables AI clients to access real-time system information such as memory and swap usage from a Linux machine via MCP tools.

Provides read-only monitoring of Apache Airflow DAGs, including listing active DAGs, fetching recent runs, and analyzing execution history and performance metrics.

MCP server that analyzes AI agent execution logs to calculate reliability scores, detect failure patterns, and suggest concrete improvements for making AI agents more reliable.

Provides 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.

Server 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.

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

MCP 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.

Monitors ML models in production for data drift and performance degradation, providing automated alerts and retraining recommendations.

Read-only MCP server for monitoring Make.com scenario errors from ChatGPT, enabling listing scenarios, viewing recent errors, and getting execution details.

Identifies resource-intensive processes on macOS across CPU, memory, and network usage, with tools for detailed process filtering and system overview.

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.