"Guide to Using LangChain Correctly" 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.

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

Using MCP to run code via e2b.

Enables AI agents and humans to read and write a git-backed knowledge base through isolated sandbox sessions, with tools for creating and closing sessions, running shell commands, listing sessions, and retrieving guide documents.

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

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.

Enables AI agents to diagnose and recover Kubernetes clusters when the API server is unreachable, using SSH access to nodes and tools like etcdctl, systemctl, and kubeadm with 63 read-only and destructive tools.

A Python-based template for creating modular command center servers using the Mondel Context Protocol that provides a structured foundation for building scalable applications with mathematical operations and modular arithmetic functions.

Gaia Protocol—a planetary DAO for global resource management using quantum-entangled ledgers and algorithmic governance.

Enables an agent to run shell commands through a JupyterLab/JupyterHub-hosted terminal, using REST API and WebSocket via Selenium for session handling, when SSH is not available.

Enables running shell commands on the local machine via MCP, using bash.

An MCP server that enables AI to execute SSH commands on remote servers using the host's OpenSSH client, supporting both configured targets and dynamic connections with request-scoped credentials.

Enables secure SSH command execution and log retrieval with intelligent summarization using local LLM (Ollama) and Model Context Protocol (MCP) standards.