"Assistance with Data Analysis on Database Data" matching MCP servers:

Enables users to create, inspect, list, and delete per-user JupyterLab servers on the UChicago ATLAS Analysis Facility Kubernetes cluster, with GPU availability and supported image listing tools.

Enables AI assistants to search, analyze, and manage Docker images on Docker Hub through standardized MCP tools, with features including security scanning, layer analysis, and image comparison.

Enables comprehensive benchmarking and performance monitoring of OpenShift clusters using OVN-Kubernetes networking through automated data collection, AI-powered analysis, and report generation. Provides intelligent insights into cluster performance, bottleneck detection, and optimization recommendations.

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 production-ready MCP server ecosystem providing Claude AI with 150+ specialized tools across enhanced memory, data analytics, security, design, and infrastructure domains with PostgreSQL, Redis, Qdrant, and Docker orchestration.

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.

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.

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

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.

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

AI-powered VMware NSX DFW microsegmentation and security. Manage distributed firewall policies, security groups, Traceflow, and IDPS with 20 MCP tools.

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.

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.

AI-powered VMware vSphere with Tanzu (VKS) management. Create and manage Supervisor Namespaces and TanzuKubernetesClusters with 20 MCP tools.

Read-only VMware vCenter/ESXi monitoring. 8 MCP tools for VM inventory, host status, datastore capacity, cluster info, alarms, events, and VM details. Code-level enforced safety — no destructive operations exist in the codebase. Supports vSphere 6.5–8.0. Works with local models via Ollama/LM Studio.

AI-powered VMware Aria Operations monitoring and capacity planning. Query metrics, manage alerts, detect anomalies, and plan capacity with 18 MCP tools.

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.