"Understanding File Systems" matching MCP servers:

Enables full lifecycle management of systemd units over D-Bus, including status, start/stop/restart, unit file authoring, journal queries, timers, and system/session information.

Enables read-only operational audits of schedulers, recurring job health, delivery failures, overdue runs, gateway/MCP health, and lock-file inventory without modifying inspected systems.

Enables secure enterprise AI agents to access internal tools like GitHub, Gmail, Calendar, file systems, databases, and knowledge bases through the Model Context Protocol, with built-in security, audit, and observability.

Provides read-only access to host system metrics (CPU, memory, disk), Docker container health/logs, and sandboxed log file analysis via MCP tools, enabling AI agents to monitor enterprise infrastructure safely.

MCP server providing lossless file reads with deduplication, per-repo token metering, and HMAC-signed context receipts. Enables auditable, vendor-neutral measurement of what an AI agent saw.

A read-only MCP server that enables LLMs to inspect and analyze ROS 2 systems through natural language, covering nodes, topics, parameters, actions, rates, QoS, and environment health. It can run without ROS 2 installed and safely surfaces runtime system state for diagnosis.

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.

Provides network and proxy diagnostics for Windows, enabling users to check GitHub reachability, system proxy settings, proxy port status, run DNS/TCP/HTTP checks, scan hosts file conflicts, and get concrete suggestions for fixes.

Enables MCP clients and AI agents to inspect a running FLECS application through its built-in REST API, including querying entities, reading components, explaining queries, and inspecting systems and performance statistics. With explicit opt-in, it also allows small reversible changes to the live ECS world.

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

Gates every AI agent tool call against your policy before it runs, then writes a hash-chained, tamper-evident record of what was decided and what happened. Anyone can verify that record offline, without your software, your systems or any key you hold.

Provides system hardware information (CPU, memory, storage, etc.) and system status (OS, network, resource usage) via MCP tools.

Privacy friendly, cookieless web analytics built MCP-first. "Add analytics to my Next.js app" → an AI agent runs the setup_analytics_for_site tool, picks the right install snippet, edits your layout file, and verifies the script is loading. OAuth onboarding, no API keys to paste.

MCP server for Beszel system monitoring that provides tools to list systems, containers, alerts, and query CPU, memory, disk, and network stats.

Enables observation-only system inspection through MCP, exposing system identity, resources, process summary, and network summary without any mutation or command execution.

Provides real-time system metrics and information through a Model Context Protocol interface, enabling access to CPU usage, memory statistics, disk information, network status, and running processes.

Enterprise AI operator evaluation MCP server. 27 tools (22 read + 5 write) for measuring, benchmarking, diagnosing, and interv ening on how human operators use AI tools across 5 canonical metrics.

MCP server for log file analysis. Gives LLMs the ability to efficiently analyze large log files without loading them into context.

Enables AI assistants to query and analyze past Claude Code sessions, providing structured insights like file changes, decisions, errors, and git history across projects.

A lightweight server that provides real-time system information including CPU, memory, disk, and GPU statistics for monitoring and diagnostic purposes.