"A service or resource for finding a coding expert" 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.

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

Provides secure access to containerized build environments for software projects, enabling AI assistants to execute builds, run tests, manage git operations, and inspect build artifacts without requiring local installation of dependencies.

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

Enables container orchestration on the local Docker daemon, allowing management of jobs and services via MCP tools.

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.

Enables AI agents to run untrusted, model-generated Python code in a locked-down throwaway Docker container with enforced isolation and resource limits. Supports starting, checking, and stopping asynchronous runs while returning structured status reports without exposing the host, network, or Docker controls.

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.

Enables AI coding assistants to search local log files, inspect Docker containers, and clean up JSON payloads through a local stdio MCP server.

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.

Gives AI assistants full control over a VPS via SSH, enabling command execution, file management, service control, Docker and firewall management.

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.

Enables asking in plain language about a Proxmox VE cluster's guests, backups, snapshots and resource pressure, and starting, cleanly shutting down or rebooting VMs and containers or taking snapshots from the same chat. Every change requires a one-time confirmation code, and no tool can delete a guest, restore a backup or roll back a snapshot.

Manage and monitor Hadoop clusters via Apache Ambari API, enabling service operations, configuration changes, status checks, and request tracking through a unified MCP interface for simplified administration. * Guide: https://call518.medium.com/llm-based-ambari-control-via-mcp-8668a2b5ffb9

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.

Self-hosted Docker sandboxes for coding agents: create a sandbox with its own Docker daemon, deploy a docker-compose stack into it, read and write its files, and get a URL for every app. Tokens can be limited to one sandbox.

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

MCP server for Android emulator automation via ADB.

Enables coding assistants to drive iOS Simulators and Android emulators or USB devices for React Native and Expo work, including taking screenshots, reading app and device logs, opening deep links, installing builds, and launching or relaunching apps. It also supports Android-specific actions such as adb reverse for Metro, opening the dev menu, and tapping or typing on screen.

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

An MCP server that provides complete Kubernetes API operations, enabling cluster management, resource CRUD, diagnostics, backup/restore, and multi-cluster configuration via natural language.

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 administrators to manage a single standalone VMware hypervisor through 63 stdio tools covering virtual machine operations, host-resource controllers, guest operations, OVF workflows, background file transfers, durable operation tracking, and optional command-line administration.

Enables control of a home lab through a single MCP server, exposing tools for Home Assistant, Portainer, Sonarr, Radarr, SABnzbd, and Jellyfin so Claude can query states, manage containers and stacks, handle media libraries and download queues, and run automations. Each service is optional and can be configured via environment variables, with a read-only mode and bearer-token-protected HTTP transport for always-on deployments.

Exposes MCP tools that start, query, signal and approve durable Temporal workflows which diagnose and remediate broken Kubernetes pods, so a crashed or restarted server simply re-attaches to the same deterministic heal instead of losing state or applying a fix twice.