Google Cloud MCP Server connects AI assistants to Google Cloud services, providing context and tools for interacting with Google Cloud resources. Built by Kristof Kowalski, it currently supports Google Cloud Logging for querying and filtering log entries, Cloud Spanner for executing SQL queries and exploring database schemas, and Cloud Monitoring for retrieving and analyzing metrics. The server authenticates with Google Cloud using either a service account key file or environment variables, and includes lazy authentication loading to prevent timeouts during initialization. It's designed for deployment with Smithery and is ideal for workflows requiring direct access to Google Cloud resources within AI conversations.
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List all billing accounts associated with the user.
Get details for a specific billing account, identified by its account ID.
List all projects associated with a billing account.
Get billing information for a specific project, identified by its project ID.
List all services available for billing.
List all SKUs available for a specific billing account.
Analyse costs for a specific project over a defined time period.
Check for any billing anomalies in a specific project.
Generate cost recommendations for a specific billing account.
Get a breakdown of costs by service for a specific billing account.
List error groups for a specific project.
Get details for a specific error group, identified by its group ID.
Analyse error trends for a specific service in a project.
Get the IAM policy for a specific project.
Test if a specific user has certain permissions on a project.
Test if a specific user has permissions on a specific resource.
Check if the user has permissions to deploy to a specific service.
List all deployment services available in a project.
Analyse gaps in permissions for deploying to a specific resource.
Query and filter log entries from Google Cloud Logging.
Query logs for a specific time range.
Perform a comprehensive search for specific log entries.
Execute SQL queries against Google Cloud Spanner databases.
List all tables in a specific Spanner database.
List all Spanner instances associated with the project.
List all databases in a specific Spanner instance.
Perform queries using natural language processing on Spanner databases.
Get the count of records that match a specific query in Spanner.
Retrieve metrics for a specific resource in Google Cloud Monitoring.
List all available metric types for a specific resource.
Query metrics using natural language.
List performance profiles from Google Cloud Profiler.
Analyse application performance to identify bottlenecks.
Compare performance trends between different deployments.
Get details for a specific trace, identified by trace ID.
List all traces for a specific project.
Find traces that are related to specific log entries.
Query traces using natural language processing.
