"How to operate a computer and execute commands" matching MCP servers:

An MCP server for tracking and managing AI command usage history using a PostgreSQL database. It enables users to log, search, and view statistics for various AI-related commands and their execution contexts.

MCP server for IBM Concert Operate that exposes the full v2 REST API as callable tools, enabling AI assistants to manage alerts, incidents, policies, runbooks, and more.

Enables local computer diagnostics by sampling CPU, memory, disk, and network activity and displaying the busiest processes in an interactive dashboard. It also supports human-confirmed process-stop proposals while keeping diagnostics local and bounded.

Enables interaction with Google Cloud services including billing cost analysis, log querying, and metrics monitoring through natural language commands. Provides comprehensive tools for managing GCP resources, analyzing costs, detecting anomalies, and retrieving operational insights.

Enables MCP clients to retrieve lab performance scores and field Core Web Vitals data for web pages via Google APIs.

Enables named, authenticated callers to run read-only introspection of a Google Cloud project and to read and write per-tenant notes that stay isolated between callers. Every request is scope-checked against a reviewed policy, rate-limited per caller, and audited without ever logging argument values.

Enables agents to fetch app reviews from Apple's App Store and Google Play per country store, newest first, filtered by date or star rating, with each scheduled run returning only reviews not seen before. It also returns a per-app, per-country rating trend row with the current rating, rating count, change since the last run, and the star split of new reviews.

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.

Checks MCP servers by URL, npm package, or official MCP Registry search, reporting availability, response speed, exposed tools, resources, and prompts. It flags changes since prior runs as breaking, warning, or info using saved snapshots.

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

Enables AI assistants to explore a PostgreSQL database, run bounded read-only SQL, inspect query plans, test hypothetical indexes, find slow queries, and check database health with compact CSV output.

Exposes a synthetic issue tracker and pipeline warehouse as callable tools so an agent can answer operational questions about tickets, pipeline health, runs, incidents, and governed metrics with every claim cited to the exact tool call it came from. All writes are proposal-only, requiring human approval through a gated apply path that logs each step for audit.

A comprehensive MCP server providing advanced Redmine project analytics, web automation via Playwright, and iTunes music integration. It enables detailed tracking of sprint metrics, bug counts, and team performance through a token-optimized tool architecture.

Enables AI agents and users to manage workspace files, monitor system metrics, take persistent notes, and retrieve weather data via MCP tools and resources.

A Model Context Protocol (MCP) server that lets an AI assistant read and operate the Lumics network monitoring platform via its REST API.

Enables read-only access to Teramind's employee-monitoring metadata, including computer and agent inventory, departments, alerts, anomaly rules, behavior policies, and monitoring profiles.

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.

MCP server for managing Proxmox VE clusters — provision VMs and containers, manage snapshots and backups, execute commands, browse storage, and monitor resources through natural language

Enables AI agents to monitor, manage, and operate a Tdarr transcoding farm by inspecting nodes, workers, queues, libraries, plugins, and job reports, and by triggering scans, requeues, and worker actions.

MCP Server for notify to telegram / weixin

Enables AI agents to query and operate a fleet of remote management devices through the RMS API in natural language, including device status, data usage, alerts, fleet summaries, and guarded reboots.

An async MCP server for Jamf Pro integration, providing AI assistants with tools for computer health analysis, inventory management, and policy monitoring.

Enables AI agents to securely manage server credentials, execute commands, inspect and rotate passwords, discover websites and containers, and access GPU/NPU status through permission-scoped MCP tools and REST endpoints.

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 MCP clients to triage SOC alerts while enforcing a trust firewall across retrieval, memory, and privileged actions. It exposes tools for alerts, logs, memory, and alert actions, with defenses that refuse risky operations in the presence of attacker-controllable content.

Enables AI assistants like Claude to deploy apps, manage databases, and operate cloud infrastructure on the ExaltByte platform using natural language commands.

Lets AI coding agents securely operate self-hosted Laravel Forge servers and sites, including deployments, logs, queue workers, environment files, commands, and maintenance tasks under per-token permissions.

An MCP server that lets AI assistants safely inspect and operate on Kubernetes clusters through natural conversation.

Enables an AI agent to manage local development environments over MCP by starting, stopping, and restarting applications and processes, reading logs with cursors, and inspecting or freeing listening ports. Exposes a fixed set of id- and port-based tools, so the agent can operate registered processes without running arbitrary commands.

Enables Claude Code users to inventory the MCP servers, skills, commands, agents and plugins installed on their machine, estimate how many tokens each one adds to every request, and switch them off per project or globally, including across other AI coding tools. It also monitors live sessions to report real token usage and the savings achieved from disabled items.