A command-line tool that enables the use of MCP with the Room protocol, allowing agents to create and interact in peer-to-peer virtual rooms for goal-oriented collaboration.

A Unity Master Control Protocol implementation that allows AI agents to control and interact with Unity, enabling them to execute code, query editor state, modify GameObjects, and capture screenshots through a WebSocket-based communication system.

A server tool for running Deep Learning models that offers Shell execution, Ngrok connectivity, and Docker container hosting with support for multiple AI frameworks including Anthropic, Gemini, and OpenAI.

An MCP (Model Context Protocol) server that integrates with the ArgoCD API, enabling AI assistants and large language models to manage ArgoCD applications and resources through natural language interactions.

A Model Context Protocol server implementation that allows AI models to interact with and manage Spinnaker deployments, pipelines, and applications through a standardized interface.

An MCP server that enables AI agents to interact with Modal, allowing them to deploy apps and run functions in a serverless cloud environment.

A simple MCP server that allows accessing and executing shell commands on a VM machine through a web-based terminal interface, with automatic tunneling to make the VM accessible from anywhere.

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

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.

A tool that dynamically generates and configures MCP servers by automatically creating necessary directories and files according to user specifications.

The sessionless code interpreter.

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

A server that connects to a Kubernetes cluster and enables management through natural language commands, supporting operations like listing resources, creating/deleting pods, and installing Helm charts.

An implementation of the Model Context Protocol for Unity Editor, allowing AI assistants to interact with Unity projects through tools for executing menu items, selecting objects, managing packages, running tests, and accessing resources.

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

An MCP server that allows managing Docker containers through natural language, enabling users to compose, introspect, and debug containers without running commands themselves.

https://github.com/abhishekbhakat/airflow-mcp-server

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

A Kubernetes-deployed server for the Model Context Protocol that enables secure communication with configurable environment variables, health monitoring, and scalable deployment on Azure Kubernetes Service.