Teradata MCP Server

Instructions

Implementation Reference

• src/teradata_mcp_server/tools/qlty/qlty_tools.py:220-256 (handler)

  Handler function implementing the qlty_rowsWithMissingValues tool. It queries the Teradata database using TD_getRowsWithMissingValues to fetch rows with missing values in the specified column and returns formatted JSON response with metadata.

  #------------------ Tool  ------------------#
  # Get Rows with Miissing Values tool
  def handle_qlty_rowsWithMissingValues(
      conn: TeradataConnection,
      database_name: str | None,
      table_name: str,
      column_name: str,
      *args,
      **kwargs
  ):
      """
      Get the rows with missing values 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_rowsWithMissingValues: 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_getRowsWithMissingValues ( ON {table_name} AS InputTable USING TargetColumns ('[{column_name}]')) AS dt;")
          data = rows_to_json(cur.description, rows.fetchall())
          metadata = {
              "tool_name": "qlty_rowsWithMissingValues",
              "database_name": database_name,
              "table_name": table_name,
              "column_name": column_name,
              "rows_with_missing_values": len(data)
          }
          logger.debug(f"Tool: handle_qlty_rowsWithMissingValues: Metadata: {metadata}")
          return create_response(data, metadata)