"Arch Linux" matching MCP servers:

MCP server — read-only log access for AI assistants. Debug your Linux server with AI, without giving the AI shell access.

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

Enables controlling your own Linux desktop machines from any MCP-capable LLM client, with opt-in agent capabilities for shell, filesystem, processes, screenshots, system info, and input injection.

Read-only MCP server for observing Linux hosts (systemd, ZFS, Docker, VMs, network, hardware, NixOS) as a graph of objects with provenance. Provides seven tools to list hosts, get status, collections, objects, evidence, lookup, and changes.

Exposes full Linux system control to AI clients via MCP tools for bash execution, file operations, and search, with configurable permissions and audit logging.

MCP server for Talos Linux cluster management via the native gRPC API

MCP server for Talos Linux cluster operations, providing typed actions for cluster configuration, bootstrap, kubeconfig, and more via talosctl.

Enables AI agents to search and retrieve academic literature from Web of Science and CNKI, with support for institutional login/SSO. Can be deployed locally on Windows or as a remote Linux server.

Local-first MCP server providing semantic search over library docs, fully offline. Single Go binary speaks MCP over stdio against a vector index pinned to the binary version. Like Context7 with the internet turned off. Apache 2.0. Linux + macOS, also available as a container image.

Persistent Linux environments for AI agents, with interactive terminals, input-wait event feedback, background tasks, file transfers, and HTTPS previews. Connect through a local stdio MCP server. Requires an agend account; bring your own agent and model.

self-hosted development harness (Go engine + CLI + desktop, Linux first) · brief → requirements → spec → plan → build → review → release · verdicts are exit codes, never model opinions · local models first (llama.cpp, vLLM) beside any OpenAI-compatible or Anthropic endpoint · operable by humans or by other agents over MCP with recorded, attributed decisions

Enables AI assistants and automation agents to query Talos Linux clusters and nodes for versions, events, service and kernel logs, resource usage, and discovery members through the Talos API, with read-only tools by default and optional node reboot when explicitly allowed.