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 your Google Cloud project.
Retrieve detailed information about a specific billing account.
List all projects associated with your billing account.
Get detailed billing information for a specific project.
List all services available for your billing account.
List all SKUs available for your billing account.
Analyse costs for a specific project over a defined time period.
Check for any anomalies in billing for a specific project.
Generate cost recommendations for a specific billing account.
Provide a breakdown of costs by service for a specific billing account.
List error groups associated with a specific project.
Get detailed information about a specific error group.
Analyse error trends over time for a specific service.
Retrieve the IAM policy for a specific project.
Test if a user has specific permissions on a project.
Test if a user has specific permissions on a resource.
Check if a user has the necessary permissions to deploy resources.
List all services available for deployment in a project.
Analyse gaps in permissions for deployment to a specific resource.
Query and retrieve log entries based on specified criteria.
Query log entries within a specific time range.
Perform a comprehensive search across logs for a specific project.
Execute a SQL query on a Spanner database.
List all tables in a Spanner database.
List all Spanner instances in a project.
List all databases within a specific Spanner instance.
Execute a natural language query on a Spanner database.
Execute a count query on a Spanner database.
Query metrics for a specific project and resource type.
List all available metric types for a specific project.
Execute a natural language query to retrieve monitoring metrics.
List all CPU profiles for a specific project.
Analyse application performance using profiling data.
Compare performance trends between different versions of a service.
Retrieve details for a specific trace ID.
List all traces associated with a specific project.
Find traces related to specific logs within a project.
Execute a natural language query to retrieve trace data.
