"How to perform commands in a terminal" 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.

A VSCode and Cursor extension that captures real-time terminal output and exposes it to AI assistants via the Model Context Protocol. It enables agents to proactively monitor logs, command execution, and errors without requiring manual copy-pasting from the user.

Terminal\[X]MCP is a Model Context Provider (MCP) server that enables intelligent terminal automation through a multi-agent system with distributed specialized roles for command execution, security validation, and real-time monitoring.

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

Enables querying and analysis of container terminal operations including vessel tracking, crane management, and productivity metrics through natural language interactions with a MySQL database.

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 assistants to query and analyze AI agent sessions from observability providers like Shepherd (AIOBS) and Langfuse, allowing users to debug agent runs, compare sessions, track performance, and analyze LLM usage patterns.

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 state-aware Terraform/OpenTofu plan evaluation against live AWS topology and CloudWatch telemetry, detecting reliability blast radius and FinOps waste before merge.

Provides real-time data for package versions, download counts, and cloud service statuses across npm, PyPI, and various service providers. It enables users to perform technical lookups and monitor service uptime through natural language commands.

MCP Server for notify to telegram / weixin

Enables interaction with Prometheus Alertmanager to retrieve, filter, and manage alerts and silences through natural language commands in Claude AI.

Bridges AI models with WinDbg to analyze Windows crash dumps and perform remote debugging through natural language queries, enabling execution of debugger commands and automated crash analysis.

Enables managing your Starlink terminal fleet through Claude AI using the Starlink Enterprise API, supporting terminal management, telemetry, data usage, and service line operations.

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 command-line interface and MCP server for managing and monitoring multiple development services through a unified terminal UI. It enables users to interact with service logs, filter messages, and control development environments directly via Model Context Protocol integration.

Monitors development commands and exposes terminal output to Claude in real-time, allowing AI assistants to see errors, logs, and stack traces without copy-pasting.

Provides AI coding agents with tools to query, search, and analyze persisted HTTP request logs, enabling efficient debugging without terminal noise.

Enables interaction with Google Search Console to query search analytics, inspect URL indexing status, and manage sitemaps. It allows users to monitor SEO performance and site health through natural language commands in MCP-compatible clients.

Gives the model visibility into the same 5-hour session, weekly, and per-model usage percentages shown in Claude Code, along with reset times. It also lets a project cap how much of the weekly limit may be spent via start/check/end budget tools that report OK, LOW, or OVER_BUDGET.