Teradata MCP Server

Instructions

Implementation Reference

• src/teradata_mcp_server/tools/base/base_tools.py:287-359 (handler)

  The handler function executing the logic for the 'base_tableAffinity' tool. It executes a predefined SQL query against DBQLObjTbl and DBQLogTbl to find tables commonly queried with the given database object, formats the results, and returns them with metadata.

  def handle_base_tableAffinity(conn: TeradataConnection, database_name: str, obj_name: str, *args, **kwargs):
      """
      Get tables commonly used together by database users, this is helpful to infer relationships between tables via SQLAlchemy, bind parameters if provided (prepared SQL), and return the fully rendered SQL (with literals) in metadata.
  
      Arguments:
        database_name - Database name
        object_name - table or view name
  
      Returns:
        ResponseType: formatted response with query results + metadata
      """
      logger.debug(f"Tool: handle_base_tableAffinity: Args: database_name: {database_name}, obj_name: {obj_name}")
      table_affiity_sql="""
      LOCKING ROW for ACCESS
      SELECT   TRIM(QTU2.DatabaseName)  AS "DatabaseName"
              , TRIM(QTU2.TableName)  AS "TableName"
              , COUNT(DISTINCT QTU1.QueryID) AS "QueryCount"
              , (current_timestamp - min(QTU2.CollectTimeStamp)) day(4) as "FirstQueryDaysAgo"
              , (current_timestamp - max(QTU2.CollectTimeStamp)) day(4) as "LastQueryDaysAgo"
      FROM    (
                          SELECT   objectdatabasename AS DatabaseName
                              , ObjectTableName AS TableName
                              , QueryId
                          FROM DBC.DBQLObjTbl /* for DBC */
                          WHERE Objecttype in ('Tab', 'Viw')
                          AND ObjectTableName = '{table_name}'
                          AND objectdatabasename = '{database_name}'
                          AND ObjectTableName IS NOT NULL
                          AND ObjectColumnName IS NULL
                          -- AND LogDate BETWEEN '2017-01-01' AND '2017-08-01' /* uncomment for PDCR */
                          --	AND LogDate BETWEEN current_date - 90 AND current_date - 1 /* uncomment for PDCR */
                          GROUP BY 1,2,3
                      ) AS QTU1
                      INNER JOIN
                      (
                          SELECT   objectdatabasename AS DatabaseName
                              , ObjectTableName AS TableName
                              , QueryId
                              , CollectTimeStamp
                          FROM DBC.DBQLObjTbl /* for DBC */
                          WHERE Objecttype in ('Tab', 'Viw')
                          AND ObjectTableName IS NOT NULL
                          AND ObjectColumnName IS NULL
                          GROUP BY 1,2,3, 4
                      ) AS QTU2
                      ON QTU1.QueryID=QTU2.QueryID
                      INNER JOIN DBC.DBQLogTbl QU /* uncomment for DBC */
                      -- INNER JOIN DBC.DBQLogTbl QU /* uncomment for PDCR */
                      ON QTU1.QueryID=QU.QueryID
      WHERE (TRIM(QTU2.TableName) <> TRIM(QTU1.TableName) OR  TRIM(QTU2.DatabaseName) <> TRIM(QTU1.DatabaseName))
      AND (QU.AMPCPUTime + QU.ParserCPUTime) > 0
      GROUP BY 1,2
      ORDER BY 3 DESC, 5 DESC
  --    having "QueryCount">10
      ;
  
      """
      with conn.cursor() as cur:
          rows = cur.execute(table_affiity_sql.format(table_name=obj_name, database_name=database_name))
          data = rows_to_json(cur.description, rows.fetchall())
      if len(data):
          affinity_info=f'This data contains the list of tables most commonly queried alongside object {database_name}.{obj_name}'
      else:
          affinity_info=f'Object {database_name}.{obj_name} is not often queried with any other table or queried at all, try other ways to infer its relationships.'
      metadata = {
          "tool_name": "handle_base_tableAffinity",
          "database": database_name,
          "object": obj_name,
          "table_count": len(data),
          "comment": affinity_info
      }
      logger.debug(f"Tool: handle_base_tableAffinity: metadata: {metadata}")
      return create_response(data, metadata)