Today, we’re expanding our ecosystem of managed remote MCP servers by introducing the Google Cloud CLI remote MCP server in preview. Powered by the popular gcloud and bq (BigQuery) command-line tools, this new server gives AI agents immediate, broad access to command-line operations for managing Google Cloud infrastructure and working with advanced BigQuery workflows securely and seamlessly. Agents are increasingly performing complex cloud operations, but standardizing how they interact with backend systems remains a challenge.
The Google Cloud CLI remote MCP server bridges this gap by packaging the versatility of hundreds of gcloud and bq commands into one single MCP server. This results in two strong benefits for the agent: Higher-level abstractions: CLI commands package complex multi-step workflows, validation checks, and high-level operations into unified commands rather than requiring multi-step API orchestration. Leverages model training: LLMs are heavily pre-trained on public command-line documentation, syntaxes, and usage examples, making CLI invocation intuitive and highly accurate for models.
Managing cloud infrastructure with AI agents traditionally requires installing and maintaining Google Cloud CLI binaries inside agent execution environments. The Cloud CLI remote MCP server bridges CLI capabilities with MCP benefits by providing an isolated execution sandbox on Google Cloud infrastructure. This solves key infrastructure challenges: Simplified dependency and runtime management: For teams building custom agents, maintaining local CLI versions and dependencies across dev, test, and production environments creates operational overhead.
Remote MCP eliminates local installations and runtime maintenance. Access for web-based agent endpoints: Web-hosted agent platforms and web interfaces (such as Gemini Enterprise and other hosted enterprise agent platforms) run in environments where users cannot control or install local packages. Remote MCP enables secure, managed access to Google Cloud CLI operations directly from these surfaces. Connecting an AI agent to your infrastructure requires strict, enterprise-ready safeguards.