CDM MCP Server

""" Configuration settings for the BERDL Datalake MCP Server. This service enables AI assistants to interact with Delta Lake tables stored in MinIO through Spark, implementing the Model Context Protocol (MCP) for natural language data operations. """ import logging import os from functools import lru_cache from pydantic import BaseModel, Field APP_VERSION = "0.1.0" SERVICE_ROOT_PATH = "/apis/mcp" class Settings(BaseModel): """ Application settings for the BERDL Datalake MCP Server. """ app_name: str = "BERDL Datalake MCP Server" app_description: str = ( "FastAPI service for AI assistants to interact with Delta Lake tables via Spark" ) api_version: str = APP_VERSION service_root_path: str = os.getenv("SERVICE_ROOT_PATH", SERVICE_ROOT_PATH) log_level: str = Field( default=os.getenv("LOG_LEVEL", "INFO"), description="Logging level for the application", ) @lru_cache() def get_settings() -> Settings: """ Get the application settings. Uses lru_cache to avoid loading the settings for every request. """ return Settings() def configure_logging(): """Configure logging for the application.""" settings = get_settings() log_level = getattr(logging, settings.log_level.upper(), logging.INFO) logging.basicConfig( level=log_level, format="%(asctime)s - %(name)s - %(levelname)s - %(message)s", ) if settings.log_level.upper() not in logging.getLevelNamesMapping(): logging.warning( "Unrecognized log level '%s'. Falling back to 'INFO'.", settings.log_level, )