"Setting up services on a Linux virtual machine" matching MCP servers:

A Linux system monitoring MCP server that provides real-time information on CPU, memory, disk, network, processes, Docker, security, and more via MCP tools.

Lets an AI assistant inspect a Linux machine through ten fixed read-only tools covering load, memory, disks, processes, ports, interfaces, systemd units, the journal, and allowlisted log files. All output is size-capped, control-character-stripped and secret-redacted, and nothing in the package can write to the system.

A comprehensive Linux system performance profiler with MCP remote invocation support, featuring advanced process profiling and flame graph generation.

MCP server that exposes Avangenio's service status by fetching and parsing status.avangenio.com/data.txt into normalized JSON.

Self-hosted Linux administration over MCP: 38 tools for processes, disks, network, systemd, journal and files, served over HTTPS. Each call runs as the caller's own OS user; root is granted per tool, limited to paths, networks and sysctl keys.

A read-only observability server that lets external agentic AI clients query CPU, memory, load, uptime, allowlisted filesystem capacity, bounded process snapshots, and permitted journald logs. It also provides a JSON system summary resource and a safe health-check prompt, with no arbitrary shell or destructive operations exposed.

Enables AI assistants to read and analyze Linux system logs—including systemd journal, syslog, kernel, application, and Docker container logs—for diagnostics and predictive analysis.

MCP server that diagnoses ML model regressions by correlating drift reports, eval runs, and deploy logs, providing evidence-cited incident reports through a set of investigation tools.

Enables AI agents to diagnose Linux server incidents by collecting and structuring system diagnostics from multiple servers via SSH, with tools for finding incident clusters, gathering context (memory, CPU, swap, etc.), and running arbitrary commands.

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.

MCP server for On-Call Health burnout analysis. Connects AI assistants to your on-call data for workload insights.

Enables analysis of JVM thread dumps to detect deadlocks, CPU spikes, pool exhaustion, and virtual thread pinning, returning a health score and interactive report link.

Read-only AMD GPU monitoring for Claude on Linux — VRAM, temperature, clocks, power, and running ML processes via rocm-smi.

Enables AI assistants to monitor and manage Linux infrastructure including services, logs, processes, disk, memory, ports, cron, nginx, Docker, and system health checks via the Model Context Protocol.

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.

Lets AI assistants query Dynatrace Managed environments — services, traces, metrics, pods, and problems — by running read-only GET requests through your already logged-in browser session, so no API tokens are needed. All traffic stays on your machine between the AI client, a local server, and a browser extension.

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

A professional-grade MCP server that enables AI assistants to monitor web services, APIs, and HTTP endpoints with enterprise-level security.

Enables management of PagerDuty incidents, services, schedules, and more directly from MCP-enabled clients, with embedded interactive UIs for incident command center, on-call management, and other features.

SSH Linux metrics, baselines, anomaly detection, and plain-English infrastructure explanations.

MCP server for managing MikroTik RouterOS devices, enabling reading device state and performing guarded write operations such as setting identity via natural language.

A read-only Model Context Protocol server that lets an LLM search Graylog logs, trace a request across services, compute exact error counts and groupings, detect deploys, and rank root-cause hypotheses across Graylog 4.x–7.x. It masks sensitive fields before any log line leaves the machine and keeps site-specific settings in configuration.

A read-only MCP server for Linux system monitoring and OS algorithm simulation, exposing tools for memory, filesystem, process, and CPU scheduling observations.

Enables Claude Desktop to interact with 57 AWS services using over 200 tools and local machine profiles. It supports multi-profile configurations and features a read-only safe mode by default to manage infrastructure like EC2, S3, and Lambda securely.

Enables stdio MCP clients to gather read-only diagnostics and incident evidence from Linux homelabs, including health, disks, services, Docker containers, logs, and confirmation-required remediation proposals.

A Model Context Protocol server that exposes all Render API endpoints and higher-level tools for managing services, deployments, databases, and more on Render.

Read-only MCP server for investigating AWS ECS deployment and runtime issues, focusing on ECS Fargate services behind an Application Load Balancer.

A comprehensive gateway and registry that unifies MCP, REST, and Agent-to-Agent services into a single secure endpoint for AI clients. It provides advanced capabilities including federation, virtual servers, rate-limiting, and OpenTelemetry observability.

PiPeFlow passively tracks AI agent workflow states using a finite state machine, providing tools for declaring, advancing, and auditing pipelines with annotations and reports.