The sessionless code interpreter. Securely run AI-generated code in stateful sandboxes that run forever.

A Python-based server enabling interaction with Proxmox hypervisors. It supports secure authentication and provides tools for managing nodes, VMs, clusters, and storage.

A powerful and flexible Kubernetes MCP server implementation with support for OpenShift.

Enables interaction with Coolify applications and resources through the Coolify API via a standardized interface, supporting application management operations such as listing, starting, stopping, restarting, and deploying.

A Model Context Protocol server that enables Docker container management through natural language interactions using a custom GPT interface.

A template for creating Model Context Protocol (MCP) servers in TypeScript, offering features like container-based dependency injection, a service-based architecture, and integration with the LLM CLI for architectural design feedback through natural language.

Allows LLMs to execute Python code in a specified Conda environment, enabling access to necessary libraries and dependencies for efficient code execution.

Enables AI interactions with a running Minecraft server inside a Docker container using RCON, allowing models to programmatically create Minecraft builds and manage the server.

An MCP server to create secure code sandbox environment for executing code within Docker containers.

Facilitates high-performance multi-client processing, enabling scalable task execution and integration of advanced agents for automation in real-world applications.

A middleware server that enables multiple isolated instances of the same MCP servers to coexist independently with unique namespaces and configurations.

Facilitates multi-client processing for high-performance operations within the DigitalFate framework, enabling advanced automation through task orchestration and agent integration.

Provides a scalable, containerized infrastructure for deploying and managing Model Context Protocol servers with monitoring, high availability, and secure configurations.

Facilitates deployment and management of services using the Model Context Protocol with a focus on high availability, scalability, and secure communication, leveraging Docker-based infrastructure, Prometheus, and Grafana for monitoring.

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.