"Understanding Workspace Control Systems or Tools" matching MCP connectors:

The agent-native cloud: database, functions, AI, storage, auth and more. 50 tools, one API key.

Integration Infrastructure Agents Actually Control

AI infrastructure design agent. Describe your app in plain English; Riley designs, prices, and deploys AWS or GCP infrastructure with generated Terraform.

Inspect and control your Northflank projects, services, jobs, and builds from your AI assistant.

Provision, SSH into, run commands on, and manage Linux VPSes from an AI agent. Pay USDC over x402 (Base) or by card over HTTP 402, a running box in under 60s. No signup, no API key to buy. This remote endpoint offers free browse/discovery, quotes, and server status.

Zero-Ops deploy of a private AI workspace to your own VPS — from your AI chat. Free and open-source.

Read-only Mac mini AI operator setup offer with queue, pricing, and buyer-route tools.

Provides tools to manage Memorystore for Valkey instances and backups.

AI first app deployment, unlike lovable or figma make, webslop.ai lets you or your ai of choice setup node.js apps or static sites in seconds. Designed be be the perfect place for you to deploy websites and apps super fast to the rest of the world and has a generous free tier.

The BigQuery remote MCP server is a fully managed service that uses the Model Context Protocol to connect AI applications and LLMs to BigQuery data sources. It provides secure, standardized tools for AI agents to list datasets and tables, retrieve schemas, generate and execute SQL queries through natural language, and analyze data—enabling direct access to enterprise analytics data without requiring manual SQL coding.

The Google GKE MCP server is a managed Model Context Protocol server that provides AI applications with tools to manage Google Kubernetes Engine (GKE) clusters and Kubernetes resources. It exposes a structured, discoverable interface that allows AI agents to interact with GKE and Kubernetes APIs, enabling them to inspect cluster configurations, retrieve Kubernetes resource YAMLs, monitor operations like cluster upgrades, diagnose issues, and optimize costs—all without needing to parse text output or use complex kubectl commands.

The Google Compute Engine MCP server is a fully-managed Model Context Protocol server that provides tools to manage Google Compute Engine resources through AI agents. It enables capabilities including instance management (creating, starting, stopping, resetting, listing), disk management, handling instance templates and group managers, viewing machine and accelerator types, managing images, and accessing reservation and commitment information. The server operates as a zero-deployment, enterprise-grade endpoint at https://compute.googleapis.com/mcp with built-in IAM-based security.

The cloud for agents. Tools for AI agents to register, build, and deploy other agents. Zero human required.

Contabo API (v1.0.0) as MCP tools for cloud provisioning, and management. Powered by HAPI MCP server

Control Plane (controlplane.com): deploy and operate workloads across AWS, GCP, Azure, and more.

Official Sevalla MCP — full PaaS API access through just 2 tools.

Ask your AI assistant a cost question. Get allocation, correlation, and explanation in one response. Costory connects Claude, Codex, or Cursor to normalized cost data across AWS, GCP, Azure, Datadog, OpenAI, and Anthropic. https://costory.io

Puter MCP lets your AI tools (Claude Code, Codex, or any other MCP-compatible client) interact with your Puter resources: managing files, publishing websites, deploying workers, and more.

InsideOut by Luther Systems — Agentic AI for cloud infrastructure design, setup, pricing, deployment, and active management. Generates Terraform for AWS and GCP. Hosted A2A agent — describe your application in plain language and InsideOut designs, costs, deploys, and manages production-ready cloud infrastructure.

Protocol-native energy infrastructure orchestration for AI data centers. Provides 46 MCP tools across 8 grid protocols (IEC-61850, DNP3, Modbus, OCPP, OpenADR, IEEE 2030.5, IEC 60870-5-104, ICCP) with 5 core API primitives: connect, dispatch, settle, comply, and intel. Enables AI agents to programmatically interact with substations, grid interfaces, and energy assets for real-time workload-grid coordination.