"Using Bing Search to Answer Questions" 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.

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.

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

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

Enables AI agents to drive genuine interactive Windows console sessions through ConPTY, so they can launch PowerShell, pwsh or CMD, send keystrokes, answer prompts, watch rendered screens and block until output matches. Multiple persistent shells can run in parallel, supporting live input, incremental reads, interrupts and window resizing.

Maps shell commands to standard MCP tools using single-file YAML specs.

Connects Claude Desktop to Windows Calculator, enabling accurate mathematical calculations using Windows' native PowerShell calculation engine.

Using MCP to run code via e2b.

A desktop launcher and local MCP workspace server that enables ChatGPT and other MCP clients to securely read, edit, search, run commands, and show changes in selected local project folders.

Enables AI assistants to execute SSH commands on network devices using natural language, supporting multiple vendors and authentication methods for automated network management.

A lightweight MCP server for file manipulation, code searching, and shell command execution, with optional semantic search using local embeddings.

Enables a remote omp client to invoke the host omp's tools over HTTP using the MCP protocol, with no LLM API calls on the host.

Ntfyx plugin 0.2.0 sends agent questions and updates to iPhone, Android and a phone-authorized Web Inbox. Local stdio MCP requires the signed CLI (current 0.1.6; minimum 0.1.3+), phone pairing and Ntfyx's hosted relay; not a standalone cloud server. Apple silicon native approvals are verified with CLI 0.1.5+; Intel Mac is unverified. MIT covers only plugin adapters.

Enables Cursor agents to ask questions and send notifications to a user via Telegram, and to require Allow/Deny approval for dangerous shell commands through Cursor hooks.

Enables an AI agent to drive a remote Linux machine over the LAN through a single TCP connection, exposing tools for shell commands, jobs, interactive PTYs, file read/write/search/transfer, process and service management, networking, packages, and power control, with optional multi-host switching. Operates without SSH or any Linux-side installation beyond one stdlib-only Python daemon, using a state-free binary protocol.

Turns Markdown files into local MCP servers, enabling users to define and run tools using simple Markdown syntax with zero dependencies.

Enables natural language command and control of remote systems across multiple platforms through Claude AI using the Model Context Protocol.

The fastest, most capable filesystem MCP server built in Rust, giving AI agents superpowers to read, search, edit, and manage files and directories.

A powerful, lightweight Model Context Protocol (MCP) server built in Python that enables Artificial Intelligence assistants (Claude Desktop, Cursor, Antigravity, Claude Code, etc.) to manage and monitor your Proxmox VE cluster using natural language.

Enables a supported web-chat AI client to control a local Windows computer through MCP using explicit, user-authorized tool calls for file, browser, shell, Git, and optional desktop operations.

Enables Claude to control tmux sessions, manage windows and panes, and search/extract text from terminal output.

An MCP server for integrating AI models with client applications, allowing for structured interactions with APIs using command-line arguments for authentication and configuration.

Remote Linux operations via SSH, exposed as an MCP server, with tools for filesystem, systemd, Docker, network, and more, using per-user AD authentication and optional sudo elevation.

Provides file system operations (read, search, list) and time queries, enabling Claude to interact with files and get time in any timezone.

Enables dynamic SSH connection to servers for real-time JVM diagnostics using Arthas, allowing operations like thread dump, heap inspection, and method watching through MCP tools.

Provides persistent SSH access to servers using OpenSSH ControlMaster multiplexing, allowing AI agents to run commands on registered hosts by name without re-entering credentials.