"How to add documentation to a project or system" matching MCP servers:

Enables monitoring of Ubuntu system metrics, Docker containers, and public IP drift, with Feishu alerting and HTTP/MCP tools for querying status, viewing history, and restarting containers.

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

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

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

Read-only MCP server for observing Linux hosts (systemd, ZFS, Docker, VMs, network, hardware, NixOS) as a graph of objects with provenance. Provides seven tools to list hosts, get status, collections, objects, evidence, lookup, and changes.

Enables LLMs to monitor system health, manage processes, execute shell commands, and inspect environment variables and directories.

Gives AI agents real-time access to system metrics, process management, and container orchestration.

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.

Provides a read-only summary of Ubuntu server status including system version, resource usage, apt updates, service health, security logs, and hardware information to AI clients via MCP tools.

Enables comprehensive system monitoring and diagnostics through 18 tools that provide detailed information about CPU, memory, disk usage, network interfaces, running processes, battery status, hardware details, and temperature monitoring. Allows users to query system information and performance metrics through natural language interactions.

Provides AI agents with tools to retrieve live system statistics (CPU, memory) and safely evaluate basic arithmetic expressions.

Provides real-time Linux system monitoring for CPU load, memory usage, disk space, and process activity. This server enables users to retrieve comprehensive performance metrics and resource utilization data through a standardized interface.

MCP server that coordinates autonomous infrastructure health monitoring agents, enabling natural-language telemetry queries and automated diagnosis, remediation, and verification.

Exposes system telemetry tools to retrieve CPU, memory, disk, battery, network, process, and GPU metrics from a local machine.

A comprehensive project management and workflow tracking system that integrates with Claude Code via MCP, automatically capturing sessions, tools, agents, and project tasks into a centralized dashboard and database.

Fetches Langfuse observability traces directly into a VS Code coding agent's context, enabling querying and viewing trace data through natural language.

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

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

Provides system diagnostic capabilities including CPU, memory, disk usage, top processes, and port status checking.

An MCP server that provides cost and reliability observability for LLM and agent workflows. It records model calls and allows querying and aggregating telemetry data through MCP tools.

Enables AI agents to monitor Docker containers, system resources, ports, and logs in real-time.

Connect AI agents like Claude, Cursor, and Gemini to historical Windows performance and privacy data gathered by the AppControl Windows app. This server enables natural language queries into CPU, GPU, and temperature history alongside system security events for deep local auditing.

Read-only MCP server for TrueNAS Scale debugging, providing k3s tools for kubectl operations and whitelisted midclt calls for system info, apps, and pools.

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.

A secure MCP proxy server with JWT authentication, SQL guardrails, rate limiting, and Kafka audit logging, enabling enterprise-grade access control for MCP clients like Cursor and Claude Desktop.

Enables interaction with Beszel system monitoring tool to query system and container statistics, manage alerts, and monitor infrastructure through its PocketBase backend.

Ask your AI agent about your MCP servers: which tools fail, how a release compares, what clients look for and do not find. Reads from mcpspan with a read token.

Enables AI agents to inspect a live Celery deployment over RabbitMQ or Redis — checking which workers are responding, their pools, concurrency and consumed queues, and how many messages are backed up in each queue — so agents can diagnose stuck or unrouted tasks. Read-only by default, with broker credentials masked in all output.

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

Provides a standardized way for MCP clients to interact with Apache Airflow's REST API, supporting operations like DAG management and monitoring Airflow system health.