"A resource for finding trading indicators" 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.

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

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

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.

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.

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.

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.

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.

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.

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

A Model Context Protocol server for managing cloud servers, particularly DigitalOcean droplets, allowing users to identify providers via IP addresses and perform operations like power management, status monitoring, and resource usage tracking.

Enables running user-supplied scripts inside resource-limited, network-isolated Docker containers built from human-reviewed Dockerfiles, with jobs driven by an outbound-only worker.

MCP server for interacting with QUADS infrastructure systems via API, enabling resource management and automation through LLM applications.

Enables management of VMware ESXi hosts and virtual machines through standardized MCP interfaces, supporting host operations, VM lifecycle, resource monitoring, and security management.

Enables management of VMware vCenter and ESXi environments, including VM operations, resource management, and automation with Ollama AI and n8n workflows.

Enables LLMs to safely execute code in isolated Docker containers with resource limits and security controls, supporting session management and automatic dependency installation.

Enables secure management of VMware vCenter 8.0+ environments through controlled operations including VM lifecycle management, snapshots, and resource discovery with built-in RBAC authorization, audit logging, and rate limiting.

Enables AI agents to dynamically spawn, route to, and manage ephemeral containerized sandboxes on Kubernetes without requiring Custom Resource Definitions or cluster-level operators.

Enables AI agents to manage Docker containers through a secure MCP interface, supporting container lifecycle operations, log inspection, resource monitoring, and system diagnostics with role-based access control.

Enables management of Proxmox Virtual Environment clusters, virtual machines, and containers through natural language interfaces. It provides 105 tools for tasks like power management, configuration, and resource monitoring with granular access control tiers.

Operates Rancher-managed Kubernetes through any MCP client with capability detection, generic resource access, and curated workflows, wrapped in an audit-logged, rate-limited, confirmation-guarded safety model.

Connects AI assistants to Linode cloud infrastructure, enabling the management of compute instances, databases, and networking resources through natural language. It provides a comprehensive suite of tools for resource orchestration, monitoring, and account management using stdio, SSE, or HTTP transports.

An MCP server that provides full lifecycle management of lightweight VMs backed by Docker containers, enabling creation, SSH access, command execution, and resource monitoring through natural language.

Enables AI agents to manage VMware vSphere virtual infrastructure through comprehensive operations including VM power control, snapshot management, resource monitoring, performance analytics, and bulk operations with built-in safety confirmations for destructive actions.

A high-performance MCP execution engine that runs tool code in isolated, resource-constrained sandboxes with context state persistence.

Enables comprehensive Kubernetes cluster management through kubectl operations and Helm chart management. Supports resource operations, logging, scaling, rollouts, and diagnostics with multiple transport modes and security features.