"Multi-platform information search across productivity and knowledge tools" matching MCP servers:

MCP server for the Agent Platform API, enabling management of sandbox environments through MCP protocol. Exposes tools to interact with sandbox lifecycle operations such as start, stop, and status checks.

Enables deploying multiple isolated Odoo MCP connector containers from a single shared codebase, each with its own configuration and credentials for different clients.

Provides read-only, governance-audited operations for OLVM and oVirt 4.5 engines, enabling inventory, health, capacity, and diagnosis queries over MCP and CLI with audit logging and budget guards.

AI-powered MCP server for managing Proxmox VE VMs and containers with built-in governance, audit logging, and reversibility.

Provides Docker management tools for AI agents, including inspecting containers, images, Dockerfiles, and Compose configurations.

Enables AI assistants to manage Coolify infrastructure including servers, applications, databases, deployments, and 80+ one-click services through 98 comprehensive tools for both cloud and self-hosted instances.

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 deployment and management of GPU workloads across multiple cloud providers (RunPod, Vast.ai) with intelligent GPU selection, resource monitoring, and telemetry tracking through Redis, ClickHouse, and SkyPilot integration.

Governed XCP-ng operations via Xen Orchestra REST — VM-health, SR-usage, backup-failure, and patch-state RCA, with unbypassable audit logging (MCP + CLI), budget/runaway guards, dry-run, and undo/rollback.

AI-powered Veeam Backup & Replication operations MCP server with tools for managing jobs, restores, sessions, and repositories, featuring built-in governance, audit logging, and safety controls.

Governed Kubernetes operations for AI agents with 15 MCP tools, audit logging, policy engine, and safety features.

Governed AI-ops MCP server for Nutanix Prism Central v4 REST API, offering 47 read/write tools for clusters, VMs, storage, network, catalog, data protection, alerts, and LCM upgrades with built-in audit, budget, and risk-tier governance.

Governed Docker + Portainer container-host operations (non-Kubernetes) — restart-loop, resource-pressure, and image/volume-bloat RCA, with guarded lifecycle writes, unbypassable audit logging (MCP + CLI), budget/runaway guards, dry-run, and undo/rollback.

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

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.

Exposes vLLM capabilities to AI assistants, enabling chat completions, model management, and platform-aware container control with automatic detection of Docker/Podman and GPU availability across Linux, macOS, and Windows.

Enables interaction with the CoreHub cloud platform to manage containers, EPFS filesystems, distributed training, and inference services through MCP tools.

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 inspection and operations on a local host through two action-router MCP tools, covering Docker daemon and container state, Compose projects, host information, allowlisted read-only command execution and file search, ZFS pools, and systemd journal logs.

An MCP server that exposes the full API of the Komodo infrastructure management platform. It enables users to manage deployments, stacks, servers, and containers through tools for inspection, configuration, and operational control.

Enables users to list GKE clusters, describe virtual machines, and retrieve billing information through MCP read tools, without applying production changes.

MCP server exposing the Dockhand API as MCP tools. Enables AI assistants to manage Docker infrastructure including containers, stacks, images, networks, and volumes across multiple hosts.

A powerful integration server that combines Netbox's network infrastructure management capabilities with MCP (Multi-Cloud Platform) functionality.

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 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

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.

Install and manage a self-hosted XNS Relayer — S3-compatible distributed object storage — conversationally over stdio. 15 tools cover prerequisites, account registration, install, claim, health, VPD configuration, S3 verification, CLI credentials, settings, restart, and backups.

Enables AI coding agents to safely run commands, install dependencies, test, and modify code inside disposable, policy-enforced Docker sandboxes isolated from the host, returning results and diffs.

Enables systematic investigation of VMware errors and events by correlating event timelines, ranking root-cause hypotheses, and suggesting next diagnostic steps.