"Resources for Learning Linux" matching MCP servers:

Linux system administration via AI agents — MCP server for managing services, processes, disk, network and logs on Linux systems.

Enables AI agents to index, search, and validate lessons learned across project repositories via a local SQLite index, providing learning-loop resources and verified-solution tracking without loading full files into conversations.

Educational MCP server with 17 tools for mathematical calculations, matrix operations, statistical analysis, and data visualization. Includes persistent workspace, cloud hosting, and safety features like restricted eval.

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

A standalone MCP server for Linux desktop control, enabling screenshots, mouse/keyboard input, app/window management, and clipboard access via a Python bridge.

Gives LLM agents spatial awareness inside Autodesk Maya, enabling scene inspection and measurement, aesthetic and engineering audits, camera planning, checkpoint/rollback safety, asset import, and viewport or render previews. Agents can also execute arbitrary Python in Maya to build and verify 3D scenes against engineering rules instead of writing blind.

A small, readable MCP learning project implemented in TypeScript that uses a local JSON notebook to demonstrate core MCP features such as tools, resources, prompts, sampling, and notifications.

MCP server that bridges Ableton Live with AI models, enabling real-time project inspection and control such as track overview, device parameters, and audio analysis.

Enables LLMs to interact with Kibana through composable toolboxes for building dashboards, managing data, and handling alerts, among other operations.

Enables AI assistants to perform controlled Linux system administration tasks like reading logs, managing services, cron jobs, WordPress, and executing sandboxed Python code, with strict security constraints.

A collection of MCP servers for managing Proxmox, Linux, Windows, Docker, npm, and Python in a homelab environment.

Provides 23 modular tools for competitive programming, including problem analysis, algorithm planning, code generation, verification, testing, code review, and learning assistance.

Enables AI agents to interact seamlessly with Splunk environments through 20+ tools for search, analytics, data discovery, administration, and health monitoring. Features AI-powered troubleshooting workflows and supports multiple Splunk instances with production-ready security.

An MCP server for read-only Linux system administration and diagnostics on RHEL-based systems via SSH. It enables users to troubleshoot remote hosts by accessing system information, services, logs, and network configurations through natural language.

Enables Linux infrastructure diagnostics and monitoring through MCP, providing tools for host, Nginx, Docker, and PostgreSQL with security and context correlation features.

The open-source, self-organizing memory for all your AI tools. Persistent memory over MCP (remember, recall, observe): background agents extract entities, resolve conflicts, and keep cited syntheses current in an append-only, encrypted, single-tenant vault.

Enables users to ask natural-language questions about a local folder's contents, including file names, sizes, and timestamps, with rollups by type and age and cleanup suggestions for stale or large files. It returns metadata only and cannot read, move, or delete files.

Express-based API for Lviv transport timetable data with a read-only MCP endpoint.

Read-only SQL MCP server for quantitative finance data (DuckDB) with stock quotes, financials, and historical K-lines, enabling cross-database JOIN queries.

An MCP server that provides AI clients with access to developer documentation via llms.txt files. Exposes tools, resources, and prompts.