Run, build, train, and deploy ML models on the cloud.

A Model Context Protocol server that allows execution of Python code within Daytona workspaces, providing a secure and isolated environment for executing and managing Python scripts.

An enhanced Windows CLI MCP server providing unrestricted system access capabilities, designed for trusted environments with full system access requirements.

A production-ready template for creating Model Context Protocol servers with TypeScript, providing tools for efficient testing, development, and deployment.

Provides isolated Docker environments for code execution, enabling users to create and manage containers, execute multi-language code, save and reproduce development environments, ensuring security and isolation.

A MCP server that can run Kubernetes commands with a given kubeconfig path and provide interpretation of the commands.

Query and interact with kubernetes environments monitored by Metoro. Look at APM, metrics, traces, profiling information with LLMs.

A powerful Model Context Protocol (MCP) server for Docker operations, enabling seamless container and compose stack management through Claude AI.

This project is intended as a both MCP server connecting to Kubernetes and a library to build more servers for any custom resources in Kubernetes.

TypeScript implementation of Kubernetes cluster operations for pods, deployments, services.