Explore MCP servers for Google Compute Engine. Integrate model context protocol solutions to streamline GCE app developm
Add new capabilities to Claude beyond text generation
Example: Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Provide Claude with access to relevant context and data
Example: Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Automate multi-step workflows combining AI and external tools
Example: Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Time estimate: 15-60 minutes depending on server complexity
Prerequisites
BugBug
Manage browser tests and suites with BugBug's software automation tester, headless browsers, and real-time error reporti
Asana
MCP server for Asana — enables Claude to interact with Asana data and workflows.
MCP Aggregator
A centralized gateway for managing multiple MCP server connections. Instead of configuring each MCP server individually
Arize Phoenix
Arize Phoenix — unified interface for managing prompts, exploring datasets, and running LLM experiments across providers
Mastra Docs
Mastra Docs: AI assistants with direct access to Mastra.ai’s full knowledge base for faster, smarter support and insight
Strong directory entry: Google Cloud Compute Engine surfaces stars and publisher context so we could sanity-check maintenance before adopting.
We evaluated Google Cloud Compute Engine against two servers with overlapping tools; this profile had the clearer scope statement.
Useful MCP listing: Google Cloud Compute Engine is the kind of server we cite when onboarding engineers to host + tool permissions.
We wired Google Cloud Compute Engine into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
I recommend Google Cloud Compute Engine for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
Google Cloud Compute Engine has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
We evaluated Google Cloud Compute Engine against two servers with overlapping tools; this profile had the clearer scope statement.
Google Cloud Compute Engine is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
According to our notes, Google Cloud Compute Engine benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
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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by googleSelect a client to integrate this server.
Claude Desktop configuration
{
"mcpServers": {
"ComputeEngine": {
"url": "https://compute.googleapis.com/mcp"
}
}
}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.
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.
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.
google/mcpThis 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.
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.
You can run these open-source MCP servers locally, or deploy them to Google Cloud (see below).
/examples/launchmybakery): A sample agent built with Agent Development Kit (ADK) that uses remote MCP servers for Google Maps and BigQuery.We welcome contributions to this repository, including bug reports, feature requests, documentation improvements, and code contributions. Please see our Contributing Guidelines to get started.
This project is licensed under the Apache 2.0 License - see the LICENSE file for details.
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.
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
Compatibility
✓ Use when
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid when
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.
Desktop Commander
Desktop Commander MCP unifies code management with advanced source control, git, and svn support—streamlining developmen