"How to create a SwiftUI app using MVVM architecture" matching MCP servers:

Enables AI agents to control and interact with a local Windows computer through authenticated MCP tools, including file operations, shell commands, process management, HTTP requests, and system/media inspection.

A FastMCP server for managing and deploying applications on Linux systems. It provides a secure interface for running system commands, managing packages, and deploying containerized applications.

Enables AI agents to safely execute privileged commands by routing them to a human approver, who runs them outside the agent's context and returns the output to the model.

Enables AI agents to securely connect to and manage remote servers via SSH, with tools for running commands, file operations, log inspection, service management, and system monitoring under configurable access controls and audit logging.

Embeds a self-hosted VS Code workbench in an MCP App, enabling collaborative editing, terminals, diagnostics, and commands in a shared workspace.

A local MCP runtime for macOS and Windows that enables ChatGPT to read, edit, search, run tests, and capture screenshots in your local project folder while keeping your source code on your machine.

MCP server that gives AI agents isolated, named Linux computers with stable IDs and lifecycle control. Supports multiple backends like Docker, Fly Machines, Modal, and E2B, with a dashboard for managing sandboxes.

Provides secure filesystem access for AI models through the Model Context Protocol with strict path validation, file operations, directory management, and system command execution within predefined directories.

A simple MCP server that exposes a terminal tool, allowing AI agents to execute shell commands.

An MCP server that enables users to execute arbitrary shell commands on their local machine and receive the output. It provides a terminal tool for running system commands through MCP-compatible clients using the Python SDK.

The m2m-mcp-server-ssh-client provides a unified MCP server interface, securely connecting via SSH to the m2m-mcp-server-ssh-server back-end which aggregates MCP servers. This setup offers secure, single-point access to diverse remote tools using robust SSH key-based authentication.

An MCP server that enables AI assistants to execute shell commands and manage files on remote servers via SSH. It supports recursive directory uploads, archive extraction, and direct file creation from text content.

A self-hosted MCP server that enables AI coding agents to read, edit, search, and run code in local projects with human review loops and policy controls.

Enables MCP-compatible AI clients to connect to a Windows machine for file operations, PowerShell execution, Git inspection, task management, memory, and skills.

Enables Claude to create and interact with real, persistent Windows terminal sessions (cmd.exe or PowerShell) through ConPTY, including sending commands, reading output, and scoped Ctrl+C interrupts without affecting other processes.

Enforces mandatory human approval before LLM agents can edit files, create files, or execute shell commands, using session tokens and audit logging.

Enables AI to execute registered system commands across platforms using a stable program + args interface, without requiring shell-specific syntax or tool discovery.

An MCP server that lets AI assistants manage an OpenMediaVault NAS over SSH using OMV's own RPC interface, covering disks, filesystems, shares, users, S.M.A.R.T. health, services, and configuration changes. It exposes a small set of generic tools to discover and call RPC methods, plus optional shell access.

Enables reading diagnostic data from remote servers over SSH using a whitelist of read-only commands, with secret redaction.

Give Claude Desktop full desktop control on Linux/X11: screenshot, mouse, keyboard, windows, clipboard, app launch. Zero-dependency MCP extension, MIT-licensed.