Retrieve detailed system information for WSL2 Linux environments by executing commands through a Linux Bash MCP Server, facilitating efficient system diagnostics and management.
Run Python code in a stateful IPython kernel within a Docker container. Maintain variables, imports, and definitions across executions for iterative workflows. Supports async code with 'await' and sequential executions with shared kernel state.
Retrieve comprehensive system details including kernel version, architecture, hostname, uptime, and memory statistics for system analysis and troubleshooting.
Retrieve details about the current platform and shell environment to identify system configurations and ensure compatibility across Windows, macOS, and Linux.
Clean the IPython kernel by resetting to a fresh state. Clears variables, imports, and definitions from memory while preserving installed packages and files. Ideal for starting fresh experiments or freeing memory after large dataset processing.
A Model Context Protocol server that connects AI assistants with the Kernel platform, enabling them to deploy applications, automate web browsers, and manage cloud resources.
Enables management of Windows servers from Linux through an MCP server with per-user installation. Provides tools to control Windows systems via API with secure credential management.