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blitzstermayank

Teradata MCP Server

qlty_distinctCategories

Extract unique values from a specific column in a Teradata database table to analyze data categories and identify distinct entries for quality assessment.

Instructions

Get the destinct categories from column in a table.

Arguments: database_name - name of the database table_name - table name to analyze column_name - column name to analyze

Returns: ResponseType: formatted response with query results + metadata

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
database_nameYes
table_nameYes
column_nameYes

Implementation Reference

  • The main handler function for the 'qlty_distinctCategories' tool. It connects to Teradata, executes TD_CategoricalSummary on the specified table and column to retrieve distinct categories, formats the results into JSON, adds metadata, and returns a response.
    def handle_qlty_distinctCategories(
        conn: TeradataConnection,
        database_name: str | None,
        table_name: str,
        column_name: str,
        *args,
        **kwargs
    ):
        """
        Get the destinct categories from column in a table.
    
        Arguments:
          database_name - name of the database
          table_name - table name to analyze
          column_name - column name to analyze
    
        Returns:
          ResponseType: formatted response with query results + metadata
        """
        logger.debug(f"Tool: handle_qlty_distinctCategories: Args: table_name: {database_name}.{table_name}, column_name: {column_name}")
    
        if database_name is not None:
                table_name = f"{database_name}.{table_name}"
        with conn.cursor() as cur:
            rows = cur.execute(f"select * from TD_CategoricalSummary ( on {table_name} as InputTable using TargetColumns ('{column_name}')) as dt")
            data = rows_to_json(cur.description, rows.fetchall())
            metadata = {
                "tool_name": "qlty_distinctCategories",
                "database_name": database_name,
                "table_name": table_name,
                "column_name": column_name,
                "distinct_categories": len(data)
            }
            logger.debug(f"Tool: handle_qlty_distinctCategories: Metadata: {metadata}")
            return create_response(data, metadata)

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