"Connecting MCP to Google Sheets for Editing and Modifications" 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 interaction with Google Kubernetes Engine (GKE) to list clusters, manage node pools, and retrieve server configurations. It includes automated scripts for deploying and testing sample applications across multiple GKE Autopilot clusters.

Enables AI assistants to manage Google Cloud Batch HPC jobs and Compute Engine VMs through conversational prompts, including submitting jobs, provisioning instances, and retrieving diagnostics.

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.

MCP server connecting Claude Code with E2B cloud sandboxes for working on any GitHub repo.

MCP server for securely discovering, pricing, renting, connecting, and releasing GPU compute instances from AI Galaxy with budget checks and two-phase approval.

A read-only MCP server that provides visibility into Parallels Remote Application Server infrastructure, policies, and sessions through the RAS REST API. It enables AI assistants to query site settings, published applications, and license status without performing any modifications.

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

Enables connecting to a Kubernetes cluster to manage resources and troubleshoot workloads with kubectl and Helm operations, including logs, scaling, port forwarding, and non-destructive mode.

Enables AI assistants to manage Google Cloud TPU VMs, including queueing, monitoring, bootstrapping, and SSH/tmux integration.

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.

Enables AI assistants to manage virtual machines via natural language, including creating, editing, and VNC control.

Enables managing Akamai Cloud (Linode) Compute Instances via MCP, with tools to list, create, view, update, delete, boot, reboot, shutdown, resize, and clone VMs. Each connecting client brings its own Linode Personal Access Token, which is passed through without being stored.

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 MCP clients to rent GPUs from ParalonCloud using natural language, including browsing available GPUs, starting and stopping rentals, and retrieving connection URLs.

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.

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.