"A tool or resource for managing a budget" matching MCP servers:

Manages resource allocation, MCP server lifecycle, and Kubernetes workers in cortex automation systems. Provides tools for requesting/releasing job resources, starting/stopping/scaling MCP servers, and provisioning/destroying burst workers with TTL management.

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.

A Model Context Protocol server that enables AI assistants to interact with Kubernetes clusters through natural language, supporting core Kubernetes operations, monitoring, security, and diagnostics.

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

Enables AI assistants to manage Docker/Podman deployments through Komodo, supporting container management, server orchestration, and infrastructure control via natural language.

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.

More than just an MCP server that covers the entire range of Docker management tasks, it helps you create workflows to easily manage your Docker environments at scale. It allows you manage multiple local or remote (TCP, TLS, SSH) docker instances and exposes things like logs and stats as resources so that you can monitor and triage all of them.

A Model Context Protocol (MCP) server that interfaces with the Apache YuniKorn Scheduler, allowing AI agents to observe and reason about Kubernetes batch workload resource management, queue hierarchies, and application states.

Enables MCP-capable clients to inventory and operate Azure resources via the Azure Resource Manager API, including resource groups, tags, and VM power, while enforcing governance controls like scoping, protected groups, location allowlists, delete gating, and confirmation.

Manages QNAP Virtualization Station (VMs, snapshots, disks, ISOs) via the QVS REST API, enabling VM lifecycle operations and resource monitoring through natural language.

Manage Docker infrastructure across multiple homelab hosts including Unraid, Proxmox, and bare metal servers. Enables container lifecycle management, log retrieval, resource monitoring, and Docker operations across your entire homelab from a single interface.

MCP server for securely discovering, pricing, renting, connecting, and releasing GPU compute instances from AI Galaxy with budget checks and two-phase approval.

Enables running arbitrary JavaScript code in isolated Docker containers with on-demand npm dependency installation, allowing for ephemeral script execution and long-running services with controlled resource limits.

Enables AI tools to manage containerized applications through Podman, supporting container lifecycle operations, command execution, log viewing, image management, and resource monitoring. Features automatic network discovery for seamless integration with MCP Discovery Hub.

MCP server for managing Docker containers, images, and Compose services via natural language, with configurable tool permissions and safety annotations.

An MCP server that exposes Proxmox VE node/cluster as tools for MCP clients, enabling management of VMs and containers including power control, resource reconfiguration, snapshots, and backups.

A gateway for Generative AI systems to interact with multiple Kubernetes clusters through Model Context Protocol, enabling comprehensive Kubernetes resource operations and multi-cluster management.

A comprehensive MCP server providing 92 tools for managing Proxmox Virtual Environment, including QEMU VMs and LXC containers.

Enables managing multiple Kubernetes clusters simultaneously with over 60 tools for cluster operations, resource management, monitoring, RBAC, storage, networking, and more through AI assistants.