"Using RAG to Provide Documentation to LLMs" 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.

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 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.

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

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.

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

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 minimal MCP server for UW Hyak (klone) that exposes tools to run shell commands and write files remotely, along with documentation resources for klone-specific utilities.

Enables LLMs to interact with remote servers via SSH, supporting command execution, file upload/download, and directory listing.

A Node.js/TypeScript MCP server that facilitates interactive communication between LLMs and users, allowing AI assistants to request user input, display notifications, and manage command-line chat sessions.

A server that enables LLMs to securely manage and execute commands on remote SSH servers.

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

A collection of Model Context Protocol servers that enable Claude Desktop to provide development assistance capabilities with filesystem, Git, shell command, and web search functionality without incurring API usage costs.

Enables LLMs to perform live debugging, dump analysis, and remote debugging by exposing Microsoft CDB capabilities through MCP. It manages cdb.exe sessions, forwards commands, and returns raw debugger output.

agentic_ssh is written in Rust and specifically engineered to provide agent-hardened, token-efficient, and asynchronous SSH orchestrations for AI agents. It automatically discovers hosts from your local SSH configurations, manages connection heartbeats, handles silent network dropouts, and supports detached background job scheduling with isolated session logging

Production-ready, zero-knowledge AI DevOps deployment, infrastructure provisioning, self-healing execution, and persistent documentation engine for VPS servers.

An all-in-one MCP server for local LLMs that provides live web access, math, shell/code execution, filesystem access, memory, and RAG over local files using LM Studio embeddings.

Bridges Claude Desktop to local Windows 10 development environments to enable repository reading, documentation searching, and isolated code execution. It provides a secure interface for running allowlisted terminal commands and scripts directly through natural language.

A Model Context Protocol server that allows LLMs to securely execute shell commands on remote Linux and Windows systems via SSH. It supports password and key-based authentication, command timeouts, and sudo elevation for administrative tasks.

A local Model Context Protocol server that allows LLMs to securely execute shell commands on remote Linux and Windows systems via SSH connections.