Forecast Storage MCP Server

# Google Cloud Project Configuration GCP_PROJECT_ID=your-project-id # Cloud SQL Instance Configuration CLOUD_SQL_REGION=us-central1 CLOUD_SQL_INSTANCE=your-instance-name CLOUD_SQL_DB=your-database-name CLOUD_SQL_USER=postgres CLOUD_SQL_PASSWORD=your-database-password-here # Optional: Google Cloud authentication # Set this to the path of your service account JSON key file for local testing # In Cloud Run, this is handled automatically by the service account attached to the service # GOOGLE_APPLICATION_CREDENTIALS=/path/to/service-account-key.json # Optional: Connection pooling (if needed in future) # CLOUD_SQL_MAX_CONNECTIONS=5 # MCP Server Configuration (for Cloud Run deployment) # Transport mode: 'stdio' for local development, 'http' for Cloud Run deployment MCP_TRANSPORT=stdio # Port for HTTP mode (Cloud Run will set this automatically) PORT=8080 # Logging Configuration # Google Cloud Logging is automatically enabled in HTTP mode (Cloud Run) # For stdio mode, standard Python logging is used # To enable Cloud Logging in local development, set MCP_TRANSPORT=http and ensure # GOOGLE_APPLICATION_CREDENTIALS points to a valid service account key