"Manim - Python Library for Animations and Math Visualization" 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.

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

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.

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.

An enhanced Python-based MCP server that enables complete VM lifecycle management and monitoring of Proxmox virtualization platforms through natural language, with 11 REST API endpoints for seamless integration.

A Model Context Protocol (MCP) server for running Genesis World simulations with integrated visualization support, using stdio transport to enable local runtime visualization features.

Enables AI clients to manage Huawei eNSP simulated network devices, execute CLI commands, apply configurations, and perform network diagnostics through natural language, with topology upload and visualization via a web UI.

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 code-mode MCP server for the Unraid 7.2+ GraphQL API that exposes search and execute tools, allowing LLM agents to introspect and call any GraphQL field via sandboxed JavaScript.

Enables MCP clients to rent GPUs from ParalonCloud using natural language, including browsing available GPUs, starting and stopping rentals, and retrieving connection URLs.

Enables systematic investigation of VMware errors and events by correlating event timelines, ranking root-cause hypotheses, and suggesting next diagnostic steps.

VMware workflow orchestration — multi-step state machine with approval gates, audit logging, and conditional execution. Coordinates cross-skill workflows like clone-and-test or compliance-scan-and-remediate across the VMware MCP skill family.

An MCP server that gives LLM agents full API access to a VMware Cloud Foundation 9.1 estate, exposing 8,931 operations through eight tools with automatic authentication, async task tracking, and write safety.

Install and manage a self-hosted XNS Relayer — S3-compatible distributed object storage — conversationally over stdio. 15 tools cover prerequisites, account registration, install, claim, health, VPD configuration, S3 verification, CLI credentials, settings, restart, and backups.

Enables AI coding agents to safely run commands, install dependencies, test, and modify code inside disposable, policy-enforced Docker sandboxes isolated from the host, returning results and diffs.

VMware vSphere compliance and hardening — read-only baseline scanning plus drift detection across CIS, DISA STIG, vSphere SCG, China DJCP 2.0, and PCI-DSS frameworks. Includes LLM-powered remediation suggestions; apply-side gated through the vmware-pilot approval workflow.