"A service for automated energy charge/discharge management" matching MCP servers:

A VMware ESXi/vCenter management server based on MCP (Machine Control Protocol), providing simple REST API interfaces for virtual machine management.

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.

Provides secure access to containerized build environments for software projects, enabling AI assistants to execute builds, run tests, manage git operations, and inspect build artifacts without requiring local installation of dependencies.

Open-source MCP server for managing Hetzner Cloud infrastructure with two management layers: * Layer 1 — Hetzner Cloud API (35 tools): Server power control, metrics, snapshots, backups, firewalls, DNS zones and records, rescue mode, server rebuild and rescale. Works even when the server OS is unresponsive. * Layer 2 — SSH (25 tools): Service management (systemd), Nginx config and reload,

Enables container orchestration on the local Docker daemon, allowing management of jobs and services via MCP tools.

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.

Gives AI assistants full control over a VPS via SSH, enabling command execution, file management, service control, Docker and firewall management.

Enables management of Verda Cloud GPU instances through Claude, allowing users to deploy spot instances, attach volumes, and monitor status. It supports automated workflows for checking availability and configuring instances with startup scripts.

A Model Context Protocol server for conducting Linux binary analysis and guest system forensics within QEMU virtual machines. It enables automated VM lifecycle management, memory dumping, and interactive debugging workflows for analyzing processes and artifacts.

Enables AI assistants to manage homelab infrastructure through automated service installation (Jellyfin, Pi-hole, Ollama, Home Assistant, Frigate NVR), VM operations, AI accelerator support (MemryX, Coral TPU, Hailo-8), and Terraform state management with SSH-based discovery and deployment.

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

An AI-powered MCP server for managing Docker infrastructure, enabling creation, deployment, and lifecycle management of containerized services with automated DNS and SSL.

Enables AI assistants to manage Docker containers and Kubernetes resources through natural language, supporting operations like container management, image building, and pod/deployment/service management.

Enables automated VPS initialization and management through SSH connections. Supports installing common services like Node.js, Nginx, and Redis, configuring domains with SSL certificates, and setting up GitHub CI/CD pipelines with deploy keys.

Enables AI agents to manage infrastructure and deploy Docker services through EasyPanel using natural language commands. It supports full lifecycle management of services, deployments, and networks while facilitating automated scaling and assisted debugging.

Provides a secure MCP interface to execute commands inside Docker Compose service containers, with real-time output capture and configurable timeouts.

Enables management of homelab infrastructure, including Docker/Podman containers, Ollama AI models, Pi-hole DNS, Unifi networks, and Ansible inventory, with built-in security checks and automated pre-push validation.

A configurable server implementation that provides MCP (Model-Controller-Protocol) functionality, supporting both Node.js and Docker environments with automated setup and configuration options.

Exposes Proxmox VE hosts as MCP tools for inventory, status, and VM/container management, running as a standalone Streamable HTTP service.

Enables LLMs to dynamically orchestrate containerized application deployments to a Kubernetes cluster, handling configuration validation, manifest generation, dry-run planning, and service endpoint extraction.