"Exploring memories or concepts related to windsurfing" 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 MCP-capable agents to discover or connect to a phone-hosted MCP service and forward SSH command execution, session, and sudo command tools over stdio.

Enables MCP-based communication with existing interactive terminal channels, such as shells or agent CLIs, by listing, reading, writing text, and sending control signals to tmux sessions without creating or managing them.

An MCP server that allows AI models to execute system commands on local machines or remote hosts via SSH, supporting persistent sessions and environment variables.

A simple MCP server that provides waiting functionality to pause until other tasks finish, with progress reporting and support for CLI or HTTP server with SSE.

MCP server providing Git-related functionalities, primarily a tool to generate diffs for Git merge commits against their first parent.

Enables ChatGPT to access a remote computer or server via an outbound-only agent, providing filesystem inspection, file editing, Git inspection, and optional shell execution through MCP.

Enables an MCP-capable agent to operate a heterogeneous cluster of Debian/Armbian Linux nodes over SSH from a single inventory, inspecting status and logs, managing packages, services, files, storage and NFS, and deploying new capabilities to nodes through installable modules. Built-in cluster tools fan out to nodes by explicit names, roles or tags with bounded concurrency, while modules can be installed on compatible nodes and run on demand or as systemd services.

Enables AI agents to securely execute remote commands via SSH or JumpServer, with flexible gateway configuration and plugin-based matchers for JumpServer login interfaces.

Enables AI agents to assess the risk of shell commands before execution, providing a probability of harm and a suggested action (auto, warn, or confirm).

Exposes every non-interactive GNU screen operation as MCP tools, letting an assistant list, create, send commands or files to, capture output from, clean up, and kill sessions. Works transparently for sessions on the local machine or on remote hosts reachable over SSH, using the recorded host registry, so remote sessions need no special transport.

Enables users to save frequently used long prompts as simple shortcuts like /review or /debug. Transform 500-word prompts into 8-character commands across any MCP-compatible platform.

A lightweight MCP server that enables natural language interaction with Kubernetes clusters, allowing management of pods, deployments, namespaces, and cluster resources through conversational queries or API endpoints.