"Resources to Become an Expert in LangChain" matching MCP servers:

Enables AI agents to explore and operate OpenShift/Kubernetes clusters, offering read-only tools for projects, pods, logs, and resources, with opt-in higher modes for scaling, restarts, applying manifests, and deletions under safe-by-default guards.

Connects AI agents to microsandbox for creating lightweight sandboxes, executing code, managing files, and monitoring resources.

Enables an assistant to control a Tandy Color Computer 3 emulated in MAME, allowing typing, disk operations, screen viewing, and state management.

A comprehensive Model Context Protocol (MCP) server that exposes 216 tools, 7 resources, and 10 runbook prompts for every OpenShift 4 cluster operation an SRE, developer, or operator could need — all driven by an LLM.

An MCP server that enables seamless management of Novita AI platform resources, currently supporting GPU instance operations (list, create, start, stop, etc.) through compatible clients like Claude Desktop and Cursor.

Enables AI assistants to manage VNG Cloud infrastructure including compute, storage, networking, and Kubernetes resources through natural language commands.

An MCP server for Kvindo Cloud that lets AI clients list, inspect, create, update, and delete cloud resources (VMs, volumes, Kubernetes, etc.) via natural language. Read-only by default, with write/delete operations gated by explicit opt-in environment variables.

Enables AI assistants to manage OpenStack cloud resources including compute, images, identity, network, and block storage via the Model Context Protocol.

This project is intended as a both MCP server connecting to Kubernetes and a library to build more servers for any custom resources in Kubernetes.

An MCP server for TrueNAS SCALE that enables read-first management of storage, system, sharing, and virtualization resources with per-user API key authentication, and optional write operations.

An MCP server that provides tools for creating and managing AWS resources using boto3, including EC2, S3, VPC, subnets, security groups, and RDS.

An MCP server that enables interaction with Kubernetes/Minikube clusters through natural language, allowing AI agents like Codename Goose to manage Kubernetes resources via the Model Context Protocol.

Enables AI models to securely query and manage virtual machines and virtualized resources via the libvirt API through the Model Context Protocol.

Enables remote Docker management over SSH via a local MCP server, providing tools to manage containers, images, Compose, and system resources.

A Model Context Protocol (MCP) server that provides safe, read-only access to Kubernetes resources for debugging and inspection. Built with security in mind, it offers comprehensive cluster visibility without modification capabilities.

An MCP server for interacting with the Proxmox Virtual Environment API, enabling management of VMs, containers, storage, and cluster resources through natural language.

This MCP provides comprehensive tools and resources for MSX software development, testing, and automation through openMSX emulator.

An MCP server that enables interaction with Kubernetes resources through natural language interfaces like Goose CLI, allowing users to get, read, and patch Kubernetes resources.

Kubernetes MCP server built into Sextant, a free open-source desktop client: agents get per-cluster permissions (off by default), every change needs a confirmation in the window, and every call is logged. Tools cover resources, logs, events, metrics, scale, restart, Helm, Flux and Argo CD.

Provides MCP multi-cluster Kubernetes management and operations. It can be integrated as an SDK into your own project and includes nearly 50 built-in tools covering common DevOps and development scenarios. Supports both standard and CRD resources.

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.

An interactive Python code execution environment that allows users and LLMs to safely execute Python code and install packages in isolated Docker containers.

Provides comprehensive management of TrueNAS SCALE instances through 278 actions across 18 categories using a token-efficient hierarchical tool design. Users can perform tasks like storage management, service configuration, and system monitoring while benefiting from built-in safety confirmations and read-only dashboard resources.

Exposes VMware vROps resources, metrics, and alerts as MCP tools, allowing an LLM client to directly query monitored infrastructure.

Enables managing Proxmox Virtual Environment resources including VMs, containers, storage, cluster status, nodes, and tasks.

Enables managing Docker containers and Portainer resources through natural language, supporting stack deployment, container operations, and environment monitoring.

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.

Enables an AI agent to view and control VMware vSphere VM consoles—screen, mouse, and keyboard—through vCenter, without installing anything in the guest.

Enables AI agents to inspect pending updates and service health for Proxmox VE VMs and containers, then take snapshots, apply official updates, reboot, and roll back under tag-based permissions and human-confirmed risky actions.

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.