// may the 4th be with you⚔️
cloud-infrastructuredeveloper-tools

Google Cloud Compute Engine

by google

Explore MCP servers for Google Compute Engine. Integrate model context protocol solutions to streamline GCE app developm

Discover official and open-source Model Context Protocol (MCP) servers from Google. This project provides an up-to-date directory of MCP servers for Google services like Compute Engine. Explore examples and resources that help you build, integrate, and extend intelligent agents using Google's ecosystem of MCP solutions—all designed to streamline context-aware app development and experimentation.

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Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.

Google-managed remote servers available15+ official Google Cloud services supportedOpen-source versions for local deployment

best for

  • / Cloud developers building on Google Cloud Platform
  • / Data engineers working with Google's database services
  • / DevOps teams managing GCP infrastructure
  • / Developers integrating Google services into AI agents

capabilities

  • / Manage Compute Engine instances and resources
  • / Query BigQuery datasets and tables
  • / Access Cloud SQL databases (MySQL, PostgreSQL, SQL Server)
  • / Control Kubernetes Engine clusters
  • / Query Firestore and Spanner databases
  • / Access Google Developer documentation

what it does

Provides access to Google's official MCP servers for cloud services like Compute Engine, BigQuery, and Kubernetes Engine. Offers both managed remote servers and open-source versions you can deploy yourself.

about

Google Cloud Compute Engine is an official MCP server published by google that provides AI assistants with tools and capabilities via the Model Context Protocol. Explore MCP servers for Google Compute Engine. Integrate model context protocol solutions to streamline GCE app developm It is categorized under cloud infrastructure, developer tools.

how to install

You can install Google Cloud Compute Engine in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server supports remote connections over HTTP, so no local installation is required.

license

Apache-2.0

Google Cloud Compute Engine is released under the Apache-2.0 license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

google/mcp

This repository contains a list of Google's official Model Context Protocol (MCP) servers, guidance on how to deploy MCP servers to Google Cloud, and examples to get started.

⚡ Google MCP Servers

Remote MCP servers

These remote MCP servers are managed by Google, and are available via endpoint. This list will be kept up-to-date as more remote servers become available.

Open-source MCP servers

You can run these open-source MCP servers locally, or deploy them to Google Cloud (see below).

💻 Examples

  • Launch My Bakery (/examples/launchmybakery): A sample agent built with Agent Development Kit (ADK) that uses remote MCP servers for Google Maps and BigQuery.

📙 Resources

Run an MCP server in Google Cloud

🤝 Contributing

We welcome contributions to this repository, including bug reports, feature requests, documentation improvements, and code contributions. Please see our Contributing Guidelines to get started.

📃 License

This project is licensed under the Apache 2.0 License - see the LICENSE file for details.

Disclaimers

This is not an officially supported Google product. This project is intended for demonstration purposes only.

This project is not eligible for the Google Open Source Software Vulnerability Rewards Program.

FAQ

What is the Google Cloud Compute Engine MCP server?
Google Cloud Compute Engine is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?
Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for Google Cloud Compute Engine?
This profile displays 70 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.5 out of 5—verify behavior in your own environment before production use.

Discussion

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MCP server reviews

Ratings

4.570 reviews
  • Naina Martin· Dec 16, 2024

    Strong directory entry: Google Cloud Compute Engine surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • Sophia Sharma· Dec 12, 2024

    We evaluated Google Cloud Compute Engine against two servers with overlapping tools; this profile had the clearer scope statement.

  • Chinedu Anderson· Dec 12, 2024

    Useful MCP listing: Google Cloud Compute Engine is the kind of server we cite when onboarding engineers to host + tool permissions.

  • Benjamin Choi· Dec 12, 2024

    We wired Google Cloud Compute Engine into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

  • Kiara Robinson· Dec 8, 2024

    I recommend Google Cloud Compute Engine for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • Chaitanya Patil· Dec 4, 2024

    Google Cloud Compute Engine has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • Piyush G· Nov 23, 2024

    We evaluated Google Cloud Compute Engine against two servers with overlapping tools; this profile had the clearer scope statement.

  • Kaira Diallo· Nov 7, 2024

    Google Cloud Compute Engine is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • Rahul Santra· Nov 3, 2024

    According to our notes, Google Cloud Compute Engine benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • William Thomas· Nov 3, 2024

    Google Cloud Compute Engine has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

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