"Hosting Supabase on Your Own Server" matching MCP servers:

Bridges the ChatGPT web UI to a local development environment over MCP, letting the model read and patch files, run real shell commands and terminals, execute tests, and control the desktop (screen, mouse, keyboard, clipboard) within user-approved folders. It adds parallel workers, goal/loop long-task control, plugin tools, and a security-hardening layer with risk-tiered shell policy, audit logging, and credential sanitization.

Enables AI assistants to diagnose, troubleshoot, and manage PC settings on Windows, macOS, and Linux through natural language commands.

Gives ChatGPT hands-on control of a local machine: reading, patching and executing code in approved project folders, running real interactive processes, managing plans and worker sub-chats, and driving the browser or desktop through user-granted permissions. Every capability is a switch inside an approved-folder sandbox, so nothing runs that the user did not explicitly enable.

Lets ChatGPT work directly on a local project by reading and editing files, running shell commands and tests, keeping terminals open, and using the user's desktop, all paired with an approved workspace folder. It also splits independent jobs across persistent workers that retain context, while riding the user's existing ChatGPT plan rather than Codex quota.

Enables AI assistants to manage remote servers via SSH with 14 commands for execution, file transfer, auditing, and monitoring.

Enables AI assistants to execute malware analysis tools on a REMnux system via Docker, SSH, or local connections. It provides automated file-type analysis, structured tool discovery, and security guardrails for streamlined malware investigation.

Enables AI assistants to manage VMware Fusion virtual machines on macOS using the vmrun CLI, including starting, stopping, and snapshot operations.

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

A secure remote server management tool based on MCP protocol, supporting SSH connections, command execution, and SFTP file transfers.

Enables AI assistants to execute SSH commands and perform token-efficient file operations on remote servers via the Model Context Protocol.

MCP server for Webmin system administration. 61 tools across 12 modules covering system monitoring, services, users, cron, packages, files, storage (SMART + LVM), security (Fail2ban), MySQL databases, Webmin ACL, and disk quotas. Four-tier safety framework with safe mode on by default. Python, MIT license, Docker and local deployment supported.

Docker container, image, volume, network, and compose management from your AI assistant.

Enables AI agents to install, remove, update, and query apt packages on Linux via MCP tools.

A Model Context Protocol server implementation that enables secure remote command execution via SSH, with features for managing and using SSH credentials.

Automates Arduino CLI workflows including dependency checks, compile/upload, serial monitoring, and safety preflight checks, all running locally on your machine.

Inspect, manage, debug, and run commands on connected Android devices and emulators through natural language.

An MCP server that enables managing Parallels Desktop virtual machines, including listing, starting, stopping, suspending, and executing commands inside VMs.

An MCP server that allows AI models to execute system commands on local machines or remote hosts via SSH, supporting persistent sessions and environment variables.

Enables interaction with lightning addresses and common lightning tools via your LLM, providing Lightning Network functionality through natural language.

An MCP server that plays local sound files on macOS using the afplay command, allowing AI assistants to trigger audio notifications after responding.