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Gemini cloud assist MCP: MCP server, setup and security

Gemini cloud assist MCP is an open-source MCP server published on GitHub that lets an AI agent understand and manage a GCP environment and troubleshoot its problems. Its repository has 70 stars and its last commit is from October 17, 2026 and it is licensed under Apache-2.0.

Actively maintained

What Gemini cloud assist MCP does

According to its repository: “MCP Server for understanding, managing & troubleshooting your GCP environment.”

The Model Context Protocol (MCP) is a standard plug between an AI agent and an outside service: once the server is connected, its tools show up in the agent, which decides when to call them. Gemini cloud assist MCP is listed under Cloud platforms, a category of 116 servers in the directory, where it ranks #49 by stars.

Topics declared by the repository: google-cloud, gemini-cloud-assist.

Installing and connecting Gemini cloud assist MCP

Distribution modes declared in the official MCP registry:

  • npm package (Node.js, usually started with npx)

It works with any MCP-compatible client (Claude Desktop, Claude Code, Cursor, VS Code, Codex and most recent agents). You add one entry to the client's MCP configuration: server name, start command or URL, environment variables. Project language: Shell.

Security: what to check

Connecting an MCP server means installing software that talks straight to your agent: it runs with your rights and the model trusts its tool descriptions. The risk therefore depends on what it can touch and how far its code can be trusted.

None of the risk signals we track (system access, secrets, missing licence, abandonment) applies to Gemini cloud assist MCP. That does not replace reading the code.

Good practice: grant only the rights needed (least privilege), require human approval for irreversible actions, and run the AI agent security check.

Project activity and maintenance

Created on September 4, 2025, the GoogleCloudPlatform/gemini-cloud-assist-mcp repository has 70 stars and 23 forks, with 0 open issues. It has more stars than 59% of the servers in the directory. It received changes this month. Version published in the registry: 0.1.1 (September 29, 2025).

Stars measure attention, not quality: a recent, heavily promoted project can collect them fast, while a useful but niche server will have few.

CoderCoder : 17.2K17.2KKubesharkKubeshark : 12.1K12.1KAwslabs MCPAwslabs MCP : 9.8K9.8KMCP server cloudflareMCP server cloudflare : 4.4K4.4KKubefwdKubefwd : 4.2K4.2KSocraticodeSocraticode : 3.4K3.4KKubernetes MCP serverKubernetes MCP server : 2.2K2.2KAzure DevOps (ADO)Azure DevOps (ADO) : 2.1K2.1KGemini cloud assist MCPGemini cloud assist MCP : 7070
GitHub stars of the most followed servers in the category (log scale); Gemini cloud assist MCP in orange. Checked October 25, 2026.

Verdict

Gemini cloud assist MCP is a reasonable choice; check the points below before connecting it.

Strengths

  • Active project: recent commit
  • Listed in the official MCP registry
  • Permissive licence (Apache-2.0)

Frequently asked questions

How do I install Gemini cloud assist MCP?

Gemini cloud assist MCP is distributed as npm package (Node.js, usually started with npx). Add it to your client's MCP configuration (Claude Desktop, Cursor, VS Code…) following the README of GoogleCloudPlatform/gemini-cloud-assist-mcp.

Is Gemini cloud assist MCP free?

The code is published under the Apache-2.0 licence and can be used free of charge.

Is Gemini cloud assist MCP safe?

No risk signal found (system access, secrets, licence, abandonment). As with any MCP server, keep rights minimal and read the code before sensitive use.

Is it an official server?

Nothing says so: it is a project published by GoogleCloudPlatform on GitHub. Check who maintains it before giving it access.

What are the alternatives to Gemini cloud assist MCP?

In the same category: MCP server cloudflare, Awslabs MCP, Terraform, and Kubefwd. MCP server cloudflare and Awslabs MCP score higher on our grid.

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Neutrality. No affiliate links. No vendor pays to be reviewed, rated or ranked. Reviews are directed by François Chollet, neutral and factual, and every data point is dated and sourced. How we score