A secure, container-based implementation of the Model Context Protocol (MCP) that provides sandboxed environments for AI systems to safely execute code, run commands, access files, and perform web operations.
A secure Docker-based environment that allows AI assistants to safely execute code without direct access to the host system by running all code within isolated containers.
A secure MCP server that provides controlled ShellJS access for LLMs, enabling AI systems to safely execute shell commands and interact with the filesystem within a configurable security sandbox.
An enhanced MCP server that grants AI assistants the ability to execute terminal commands on a user's system with improved security controls, designed for use in controlled environments.
A flexible server that enables communication between AI models and tools, supporting multiple MCP servers and compatible with Claude, MCP Dockmaster, and other MCP clients.