"Resources for Learning Python Coding" matching MCP servers:

Enables AI assistants to manage OpenStack cloud resources including compute, images, identity, network, and block storage via the Model Context Protocol.

An interactive Python code execution environment that allows users and LLMs to safely execute Python code and install packages in isolated Docker containers.

MCP server that gives AI agents isolated, named Linux computers with stable IDs and lifecycle control. Supports multiple backends like Docker, Fly Machines, Modal, and E2B, with a dashboard for managing sandboxes.

A Node.js application that provides a JSON-RPC interface to interact with CO2 sensor data, working in both simulation mode and with real Raspberry Pi Pico hardware connections.

Connects AI agents to microsandbox for creating lightweight sandboxes, executing code, managing files, and monitoring resources.

MCP server that integrates with Coolify to let AI assistants manage Coolify instances via a clean toolkit wrapping the official REST API.

Enables managing RunPod compute for the Learning-to-Swim replication through natural language, including pod lifecycle, SSH/rsync file transfer, detached training jobs, and supervised runs with cost guardrails.

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

A Python-based MCP server for interacting with Proxmox hypervisors, enabling management of nodes, VMs, containers, and executing commands via QEMU Guest Agent.

Enables interaction with Proxmox VE for managing VMs, containers, storage, and cluster resources via natural language through the Model Context Protocol.

Enables AI models to securely query and manage virtual machines and virtualized resources via the libvirt API through the Model Context Protocol.

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 server for interacting with the Proxmox Virtual Environment API, enabling management of VMs, containers, storage, and cluster resources through natural language.

This MCP provides comprehensive tools and resources for MSX software development, testing, and automation through openMSX emulator.

An MCP server that enables interaction with Kubernetes resources through natural language interfaces like Goose CLI, allowing users to get, read, and patch Kubernetes resources.

Exposes VMware vROps resources, metrics, and alerts as MCP tools, allowing an LLM client to directly query monitored infrastructure.

Enables managing Proxmox Virtual Environment resources including VMs, containers, storage, cluster status, nodes, and tasks.

Enables safe Python code execution in isolated Docker containers through the AgentRun framework. Provides automatic container lifecycle management and comprehensive error handling for secure and reproducible code execution.

A Model Control Protocol server that extends AI assistants with Kubernetes operations capabilities, allowing for managing deployments, pods, services and other K8s resources.

Enables managing Docker containers and Portainer resources through natural language, supporting stack deployment, container operations, and environment monitoring.