"Understanding Vite running status in terminal commands" matching MCP servers:

Provides AI agents with real-time ground truth about what's actually running on the machine, including live agent sessions, listening TCP ports, loaded daemons, and system stats. It reads directly from the OS via fixed commands, ensuring agents never rely on stale docs or transcripts.

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.

Model Context Protocol server for monitoring Operational Status of major digital platforms in Claude Desktop.

Aggregates status of multiple SaaS providers into a single MCP server, enabling AI agents to check service health and incidents via tools like list_services, get_status, and check_all.

Enables web audits for performance, security, SEO, and DNS, returning structured improvement prompts for AI assistants.

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

Enables real-time monitoring of F5 Cloud service status, including 148+ service components, active incidents, and scheduled maintenance windows with intelligent caching and dual data source reliability.

Monitor the real-time status of 200+ popular APIs and services. Check if services like GitHub, Stripe, AWS, and Slack are experiencing outages or degraded performance directly from your AI assistant.

Lets an assistant read recorded production AI agent runs — steps, model and tool calls with arguments, and outcomes — along with the findings of comparison runs that checked a prompt or model change against those recordings, and verify a signed evidence bundle offline with no account or network. It is strictly read-only: no tool starts a replay or comparison, so nothing can spend money or act without a person deciding.

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 read-only inspection of local coding-agent sessions across Claude Code, OpenCode, Cursor, and Codex, including running status, topics, todos, and transcripts, without writing or sending messages.

Live .NET runtime diagnostics for AI assistants. Ask Claude to diagnose memory leaks, GC pressure, LOH fragmentation, and thread starvation in any running .NET process — no code changes required.

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.

RunBeacon is an MCP server that turns long-running local and SSH commands into tracked jobs. It provides event-driven monitoring, a live dashboard, and a resident daemon for reliable execution and cancellation.

Enables AI assistants to drive the UTMStack SIEM/XDR platform for triaging alerts, searching logs, running SQL, managing incidents, inspecting agents, creating/deleting correlation rules, managing data filters, and running commands on endpoints.

Headless MCP server for Eclipse MAT that enables analyzing Java heap dumps using built-in commands, OQL queries, and predefined reports.

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

Enables AI agents to query and monitor service status, latency, and performance through configurable checks (HTTP, TCP, SSL, keyword, JSON-path) and exposes tools for listing services, retrieving metrics, and running on-demand checks.

An MCP server that exposes Home Assistant's REST and WebSocket APIs as 182 tools, enabling clients like Claude Code to control lights, climate, media, automations, and more. It also provides a status dashboard and supports running as a Home Assistant app or container.

Surface Claude Code token usage, estimated cost, and plan-limit status in any MCP client. Enables agents to query usage data from local logs and Anthropic API.