Interact with Google Cloud services and manage your cloud resources.
Google Cloud MCP MCP server is a hosted integration for AI assistants that speak the Model Context Protocol. Interact with Google Cloud services and manage your cloud resources.
The gcloud Model Context Protocol (MCP) server enables AI assistants to easily interact with the Google Cloud environment using the gcloud CLI. With the gcloud MCP server you can:
Being a remote server, there is no local install. You register the endpoint with your client, authorise it once, and the tools appear.
Once Google Cloud MCP is connected, these are the calls the assistant has available:
gcloud — run_gcloud_commandobservability — list_log_entriesstorage — list_objectsbackupdr — list_backup_vaultsPrerequisites — The Prerequisites tool exposed by this serverThis sits in the cloud and infrastructure group, where several servers overlap in what they claim to do but differ sharply once you actually set them up. Google Cloud MCP's toolset — gcloud, observability, storage and 2 more — is a fair guide to whether it matches your workflow.
This entry was verified against Google Cloud MCP's own documentation before publication; SyncDev keeps the directory reviewed rather than auto-generated.
| Tool | What it does |
|---|---|
| gcloud | run_gcloud_command |
| observability | list_log_entries |
| storage | list_objects |
| backupdr | list_backup_vaults |
| Prerequisites | The Prerequisites tool exposed by this server. |
{
"mcpServers": {
"github-com-googleapis-gcloud": {
"command": "npx",
"args": ["-y", "@google-cloud/"]
}
}
}Add to claude_desktop_config.json, then restart Claude Desktop.
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Stop letting your assistant hallucinate n8n node parameters — this server hands it the real schemas, templates and validation.
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