"A FastAPI server for interacting with the GitHub API for file operations and repository management" 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.

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

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

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.

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

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

Expose Nutanix V4 APIs as tools callable by AI assistants — Claude, Cursor, and any MCP-compatible client.

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,

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 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.

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

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.

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.

Enables AI-assisted management of vCenter Server and standalone ESXi hosts, including lifecycle, deployment, guest operations, cluster management, datastore browsing, alarms, and investigations through natural language.

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.

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.

MCP server for Pterodactyl and Pelican game server panels. 73 tools for server management, power control, file operations, backups, schedules, databases, users, nodes, and eggs.

MCP server for managing VMware Horizon VDI environments via the Horizon 8 REST API, enabling AI agents to monitor sessions, manage pools, and perform operations like logoff, reset, and image push with safety previews and audit logging.

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.