"A search query to learn about Google Cloud services" matching MCP servers:

Enables deployment of a Model Context Protocol server with SSE transport on Google Cloud Run for integration with Antigravity.

MCP Server for Google Cloud Healthcare API enables Agentic AI for a variety of FHIR-based digital health solutions, from smarter clinical workflows for Health Systems to Pre-Auth frameworks for Payers!

Enables users to record Windows desktop and browser workflows once and generate replayable Cursor Skills, using Playwright MCP and Windows Computer MCP for semantic, non-coordinate replay.

MCP server that enables an agent to spawn sub-agents (a crew) via a local tool, allowing delegation of large tasks to parallel workers with a human approval gate and efficient token usage.

Enables MCP-compatible AI agents to deploy applications to Google Cloud Run by providing tools for deploying code, listing services, and managing Google Cloud projects.

Enables AI agents to access DDG's payable services including checkout/payment conformance, MCP/tool security audits, agent-discovery repair, and buyer-agent smoke probes, with structured payment challenges.

Reference MCP server for IOX Cloud — a deployment platform for MCP servers and AI agents. Deploys to 300+ edge locations via Cloudflare Workers for Platforms with per-tenant V8 isolation, built-in OAuth 2.1, and usage tracking. This repo demonstrates a minimal MCP server that introspects the IOX Cloud platform (tools: get_platform_info, list_templates, estimate_cost, check_slug_available).

Enables connecting multiple business tools behind a single managed MCP endpoint with per-connector permissions, dispatch, and audit records.

A dedicated server for Oracle Cloud Infrastructure (OCI) Core Services that enables management of compute instances and network operations with LLM-friendly structured responses.

Universal search engine for AI agents. Discover products, services, and businesses across every category. 10 MCP tools, zero LLM calls, millisecond responses.

Enables AI assistants and other MCP clients to launch and steer Cursor Cloud Agents on repositories or as repo-less research tasks, including model selection, mid-run follow-ups, cancellation, result retrieval, and run listing. Also exposes authentication checks and per-agent or per-run token usage and cost reporting.

A Model Context Protocol (MCP) server that integrates Claude with the Terraform Cloud API, allowing Claude to manage your Terraform infrastructure through natural conversation.

Enables management of Verda Cloud GPU instances through Claude, allowing users to deploy spot instances, attach volumes, and monitor status. It supports automated workflows for checking availability and configuring instances with startup scripts.

Enables AI-powered web searches using Google's Gemini 2.5 models with Google Search Grounding. Supports multiple Gemini models (Flash, Flash-Lite, Pro) with configurable thinking budget and web search capabilities.

Enables Claude to use Google Gemini as a secondary AI through MCP for large-scale codebase analysis and complex reasoning tasks. Supports both Gemini Flash and Pro models with specialized functions for general queries and comprehensive code analysis.

Enables AI agents to perform web search, extraction, and research across multiple provider backends with persistent multi-key rotation and auditable routing. Supports MCP, CLI, and Agent Skill entry points.

Enables MCP clients to interact with A2A agents through four ordinary tools, translating agent discovery, messaging, task reading, and cancellation between the A2A and MCP protocols, with support for the tasks extension.

Enables parallel research across multiple cheap AI worker models, splitting a question into sub-questions and synthesizing one sourced answer with references.

Enables a single user to let ChatGPT read and control a dedicated Chromium browser running on their own server, with tab, navigation, and browser-action tools plus manual approval safeguards.

An MCP server that turns a one-sentence idea into working, tested code using a pipeline of six AI agents, with optional deployment.