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

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 read-only inspection and diagnosis of Windows, macOS, and Linux machines through eight diagnostic tools covering system profiles, baselines, disk health, startup audits, driver context, and upgrade planning, with voice summaries and a web simulator. It enforces an R0-R3 risk model in code so only safe R0 evidence collection is automatic while riskier actions remain manual guidance.

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.

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 precise measurement of live HTTP and WebSocket services while maintaining an append-only, evidence-based ledger of claims that agents can query with explicit timestamps, staleness indicators, and instructions for re-verification.

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

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

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

A production-oriented reliability, benchmarking, and evaluation system that layers multi-version protocol negotiation, adaptive streaming, connection pooling, and resilience onto an MCP agent runtime.

Provides governed MCP tools for querying optionally restricted Microsoft Sentinel/Log Analytics tables and optional Defender XDR hunting data, retrieving incidents and entities, and—for agent identities only—adding attributed incident comments, with Entra ID authentication, KQL validation, rate limits, and redacted audit logging.

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

A Model Context Protocol server for Zoho Site24x7 that uses a JavaScript sandbox to execute API calls, enabling management of monitors, accounts, and MSP/BU tenancy through natural language.

Enables AI agents to inspect, debug, and operate Redis Queue (RQ) queues, jobs, and workers, with access gated by read-only, write, or admin modes.

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 any MCP-compatible agent to query, diagnose, map, and operate Elasticsearch or OpenSearch clusters via REST, with read-only defaults and layered safety controls.

Checks what local coding agents such as Claude Code, Codex and Cursor really did: files changed, commands run and test results read from test output, not the agent's word. Unclear test results can be double-checked by Laya (on your computer) or TypeSafe's Jev (cloud, your own API key). Read-only.

Enables agents to score, inspect, and gate tool calls before they execute, resolving shell commands the way a shell would in order to block destructive actions and detect multi-step attack sequences. It also redacts credentials and PII in either direction, requires signed single-use approval tokens for high-impact actions, and keeps a tamper-evident audit trail.

Enables LLMs to directly query a Matomo analytics instance, execute reporting methods, fetch historical trends, report metadata, and dynamically generated chart images through typed MCP tools.

Provides access to Prometheus metrics and queries, allowing AI assistants to execute PromQL queries and analyze metrics data through standardized MCP interfaces.

Enables MCP-compatible applications to execute CrowdStrike NGSIEM security event searches with query validation and schema discovery.

Enables AI incident-response agents to connect over MCP to a simulated service environment, receive alerts, gather diagnostic evidence, execute safe SOP actions, and verify recovery.

Enables comprehensive integration with Azure AI services including OpenAI, Cognitive Services, Computer Vision, and Face API through a mission-critical MCP server. Provides enterprise-grade reliability with high availability, observability, chaos engineering, and secure multi-region deployment capabilities.

Enables AI clients like Claude to triage, investigate, and operate Icinga installations through natural language, integrating with Icinga's REST APIs and providing deep awareness of monitoring plugins and historical performance data.

Enables grading a website's security headers with per-gap fixes and a README badge, and analyzing logs, code, configs or suspicious messages to determine what happened, how severe it is, and what to fix first. Requests are masked for sensitive data and automatically retried across multiple AI providers when one refuses, subject to a defensive-use-only policy.

Enables AI agents to read protected computers and their check-ins, computer groups, approval requests, the unified audit log, and child organizations through a zero-trust endpoint security portal API. Every operation is read-only, with credentials supplied per request as headers and never stored.

Enables AI clients to safely query and operate SQL databases with per-statement risk grading, two-phase confirmation for dangerous operations, and access-level enforcement. Every action is recorded in a tamper-evident hash-chain audit log with integrity verification.

Enables Codex users to check MCP connectivity and inspect recent Computer Use call records, paired hook events, and missing or conflicting observations for reliable app and window targeting.

Let AI agents observe and operate your Hatchet workflows: runs, logs, workers, metrics, plus trigger/cancel/replay.

Enables AI assistants to operate and monitor Windows workspaces through native tools for filesystem operations, PowerShell execution, background tasks, Windows services, GPU telemetry, PDF generation, and a built-in web gateway/dashboard.

Enables AI agents to safely and audibly operate PostgreSQL databases and their Docker environments, offering schema inspection, guarded queries, migrations, performance diagnosis, and container management tools.