get_daily_battery_usage_patterns
Analyze daily battery consumption patterns for Tesla vehicles to understand energy usage trends and optimize charging schedules.
Instructions
Get the daily battery usage patterns for each car. Analyzes battery consumption patterns throughout the day.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Output Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Implementation Reference
- src/tools.py:52-56 (registration)Tool definition registration including name, description, and associated SQL query file 'daily_battery_usage.sql'.
ToolDefinition( name="get_daily_battery_usage_patterns", description="Get the daily battery usage patterns for each car. Analyzes battery consumption patterns throughout the day.", sql_file="daily_battery_usage.sql", ), - main.py:22-29 (handler)Handler factory that creates the execution function for the tool by running the SQL query from the specified file synchronously.
def create_tool_handler(sql_file: str): """Factory function to create tool handlers""" def handler() -> List[Dict[str, Any]]: return db_manager.execute_query_sync(sql_file) return handler - main.py:32-39 (registration)Dynamically generates and registers the tool handler with the MCP server using the @mcp.tool decorator for STDIO transport.
for tool_def in TOOL_DEFINITIONS: tool_func = create_tool_handler(tool_def.sql_file) tool_func.__doc__ = tool_def.description tool_func.__name__ = tool_def.name # Register the tool with the MCP server mcp.tool()(tool_func) - src/database.py:27-34 (helper)Core helper function that reads the SQL file and executes the query on the database, returning results as list of dicts.
def execute_query_sync(self, sql_file_path: str) -> List[Dict[str, Any]]: """Execute SQL query synchronously""" sql_query = self.read_sql_file(sql_file_path) with psycopg.connect(self.connection_string, row_factory=dict_row) as conn: with conn.cursor() as cur: cur.execute(sql_query) return cur.fetchall() - main_remote.py:118-127 (handler)Async handler for predefined tools in HTTP transport server, resolves tool definition and executes corresponding SQL query.
async def execute_predefined_tool(tool_name: str) -> List[Dict[str, Any]]: """Execute a predefined tool by name""" if not app_context: raise RuntimeError("Application context not initialized") tool = get_tool_by_name(tool_name) return await app_context.db_manager.execute_query_async( tool.sql_file, app_context.db_pool ) - main_remote.py:179-186 (registration)Registers the tool schema (name, description, empty input schema) in the list_tools handler for HTTP transport MCP server.
for tool_def in TOOL_DEFINITIONS: tools.append( types.Tool( name=tool_def.name, description=tool_def.description, inputSchema={"type": "object", "properties": {}}, ) )