"Real-Time Stock Options Data for All NASDAQ Stocks" matching MCP servers:

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.

A Model Context Protocol server for the resQ emergency response system that integrates with digital twin simulations and coordination engines. It allows users to trigger simulations, generate deployment strategies, and monitor real-time drone status for incident response analysis.

A Linux system monitoring MCP server that provides real-time information on CPU, memory, disk, network, processes, Docker, security, and more via MCP tools.

Control and automate FlexSim simulations through AI assistants like Claude, enabling manufacturing and warehouse digital twin analysis, parameter studies, and real-time model manipulation via tools for opening models, running simulations, evaluating FlexScript, and exporting results.

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

MCP server that gives Claude Code real-time visibility into local infrastructure — Docker containers and system health.

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

Enables AI assistants to create isolated Kubernetes Pod sessions for real-time shell command execution, file management, and Node.js code execution, with automatic TTL-based cleanup.

Enables AI agents to create, drive, checkpoint, reset and delete resettable Windows and Ubuntu desktop VMs on Apple Silicon Macs, giving them real desktops to click, type and screenshot in plus shell commands, file transfer and port forwarding. All processing is local, so agents can work in isolated guests without leaving the Mac.

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

Enables AI models to interact with Harbor container registries to manage projects, repositories, and system configurations in real time. It provides a suite of tools for monitoring health, retrieving statistics, and performing searches across registry data.

Enables VMware vCenter management via MCP, adding real-time and historical performance monitoring, VM lifecycle operations, snapshots, ISO mounting, and network/host management through natural language.

Enables remote container security monitoring and management through Docker API and SSH connections. Provides real-time container monitoring, security analysis, event tracking, and comprehensive security scanning for containerized environments.

An MCP server that gives AI assistants real-time access to your homelab infrastructure. It enables querying node status, managing Docker containers, controlling Proxmox VMs, and inspecting OPNsense firewall state through natural conversation.

Exposes MCP tools that enable remote LLMs to query local Docker containers, OS processes, and system services in real time.

Enables real-time monitoring and control of any Webots robot simulation, providing access to robot state, sensors, camera feeds, and simulation controls (pause, resume, reset) through natural language.

Enables users to manage Hetzner Cloud resources including servers, load balancers, and volumes through natural language commands. It facilitates infrastructure operations such as resource creation, security configuration, and real-time pricing queries within AI-powered environments.

Enables interaction with Kubernetes clusters through 32 specialized tools for managing resources, deployments, and services. Provides both CLI and web interfaces for real-time Kubernetes operations powered by Google Gemini.

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.

GenieACS-MCP is a Go-based MCP server that bridges any GenieACS (TR-069 ACS) instance, exposing device data, firmware management, and CPE actions (reboot, parameter refresh, firmware download) over JSON-RPC

AI-powered VMware storage management for vSphere. Manage datastores, iSCSI targets, and vSAN via natural language with 11 MCP tools.

MCP server for managing Proxmox VE resources, VM/CT lifecycle, snapshots, backups, and clones via natural language.

Enables unified administrative control over Cloudflare, Porkbun, Docker, Proxmox VE, Nginx Proxy Manager/NPMPlus, Uptime Kuma, Authentik, and Coolify. Exposes service discovery and action execution through three MCP tools with roughly 150 cataloged operations for managing DNS, containers, VMs, proxies, monitors, users, and related infrastructure.

Connects Claude Desktop to any Kubernetes cluster, enabling natural language queries for diagnostics and operations such as listing pods, viewing logs, scaling deployments, and more.

A self-hosted MCP server providing a governed interface for AI agents to interact with local Docker infrastructure, featuring a two-phase confirm protocol for state-changing operations and append-only audit logging.

MCP server for Proxmox VE and Proxmox Datacenter Manager, covering every API endpoint via six consolidated tools for list, describe, and call operations with a read-only safety gate.

A read-only MCP server for Proxmox VE that provides AI assistants with structured visibility into cluster nodes, guests, storage, and Docker workloads. It is designed to prevent any mutating operations by construction.

MCP server for controlling PNETLab v6 network labs via natural language, enabling topology creation, node management, config push, console interaction, and link fault injection.

Enables AI agents to interact with Kubernetes clusters through progressive disclosure, where agents discover TypeScript modules via filesystem, write and execute code, and receive summarized console output for cluster management tasks.