"Steps to Internationalize and Localize My Application with Translations" matching MCP servers:

Enables ChatGPT web to read local files, search code, run shell commands, and drive a local Codex CLI via an official MCP connector, with human approval for risky commands and full audit logging.

An MCP server that enables large language models to connect to remote servers via SSH, execute commands, and transfer files securely.

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.

A minimal MCP server that exposes a run_command tool over stdio, enabling command execution within a Docker container.

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.

Memory bank with Server as SSH support for central knowledge base

A local MCP bridge that lets ChatGPT chat mode operate the user's own computer, running project, file, and shell tasks through a local executor and returning progress and results to the conversation. It also coordinates Codex sessions (persistent or one-off) and other agent CLIs as sub-agents.

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.

Enables a Claude Code cloud session to run shell commands inside a chroot jail on your own computer and to call the MCP servers already installed there, with every request authenticated and relayed over a Cloudflare quick tunnel so no router port is opened and no SSH key or tunnel is ever handed to the cloud VM.

A demo MCP server that enables users to interact with various tools through natural language, including note management, weather queries, calculations, file operations, and shell commands. Uses Ollama for intent detection and structured command parsing from free text input.

Enables remote server control via SSH through Claude, supporting command execution, file transfers, and multi-server management with both standard and streamable HTTP protocols.

Enables AI clients to securely execute remote commands and transfer files over SSH through standardized MCP tools, with multi-host management, flexible authentication, and an admin console.

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

Enables AI-assisted development tools like Cursor, Cline, and Windsurf to request user confirmation before acting, running shell commands and displaying their output inside a Qt feedback window that returns user notes and logs to the model. This human-in-the-loop loop lets the assistant consolidate many speculative tool calls into a single feedback-aware request, saving API usage and improving accuracy.

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 custom Model Context Protocol server that gives Claude Desktop and other LLMs access to file system operations and command execution capabilities through standardized tool interfaces.

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

MCP server for inspecting IBM Liberty/WebSphere application servers over SSH, enabling reading sanitized configs, performing health checks, and searching logs remotely.

Runs commands on machines you cannot SSH into by publishing steps to a transport the far side already reaches (git, file share, S3, relay), then reads back a log with every line timestamped in UTC. Seven tools cover send, status, logs, stall detection and a pre-flight check.

Provides AI assistants with the ability to control Linux desktop environments through tools for file management, application launching, and system operations like clipboard access. It includes a multi-level security model to manage permissions for safe, elevated, and restricted actions.

MCP server for running shell commands on a Linux development board via UART serial.

MCP server that enables reading and writing macOS system preferences and application settings through the defaults system.

A Model Context Protocol server that enables clients to interact with a system terminal running in an Electron application, allowing for executing commands, managing terminal sessions, and retrieving output programmatically.

Enables AI agents to manage system updates, application installations, and remote host orchestration through MCP tools.

Enables server operations and AI application deployment via 16 MCP tools, including container management, disk diagnostics, and GitHub repository search with one-click deployment, through natural language.

A server that enables programmatic interaction with an already running Abaqus/CAE GUI application, allowing users to execute Python scripts and retrieve message logs through the Model Context Protocol (MCP).

Wraps Oh My Pi built-in tools (read, write, edit, bash, grep, etc.) as MCP tools, enabling file operations, shell commands, web search, and agent coordination.

It enables MCP-compatible AI clients to run local device, filesystem, shell, PowerShell, Git, browser, HTTP, clipboard and application actions on a Windows PC and a paired Android phone, with session-based device routing. Sensitive operations are gated behind configurable one-use approvals and recorded in a local SQLite audit.

Enables AI agents to interact with Windows operating systems through native UI automation, file navigation, application control, and system commands. Provides seamless integration between LLMs and Windows environments for tasks like clicking, typing, launching apps, and capturing desktop state.