base_columnDescription

Instructions

Implementation Reference

• src/teradata_mcp_server/tools/base/base_tools.py:167-243 (handler)

  The handler function that implements the core logic of the 'base_columnDescription' tool. It executes a SQL query against DBC.ColumnsVX to retrieve detailed column information (name and decoded type) for tables/views matching the provided database_name and obj_name patterns (using LIKE with wildcards if empty). Returns formatted JSON data with metadata.

  def handle_base_columnDescription(conn: TeradataConnection, database_name: str | None, obj_name: str, *args, **kwargs):
      """
      Shows detailed column information about a database table via SQLAlchemy, bind parameters if provided (prepared SQL), and return the fully rendered SQL (with literals) in metadata.
  
      Arguments:
        database_name - Database name
        obj_name - table or view name
  
      Returns:
        ResponseType: formatted response with query results + metadata
      """
      logger.debug(f"Tool: handle_base_columnDescription: Args: database_name: {database_name}, obj_name: {obj_name}")
  
      if len(database_name) == 0:
          database_name = "%"
      if len(obj_name) == 0:
          obj_name = "%"
      with conn.cursor() as cur:
          query = """
              sel TableName, ColumnName, CASE ColumnType
                  WHEN '++' THEN 'TD_ANYTYPE'
                  WHEN 'A1' THEN 'UDT'
                  WHEN 'AT' THEN 'TIME'
                  WHEN 'BF' THEN 'BYTE'
                  WHEN 'BO' THEN 'BLOB'
                  WHEN 'BV' THEN 'VARBYTE'
                  WHEN 'CF' THEN 'CHAR'
                  WHEN 'CO' THEN 'CLOB'
                  WHEN 'CV' THEN 'VARCHAR'
                  WHEN 'D' THEN  'DECIMAL'
                  WHEN 'DA' THEN 'DATE'
                  WHEN 'DH' THEN 'INTERVAL DAY TO HOUR'
                  WHEN 'DM' THEN 'INTERVAL DAY TO MINUTE'
                  WHEN 'DS' THEN 'INTERVAL DAY TO SECOND'
                  WHEN 'DY' THEN 'INTERVAL DAY'
                  WHEN 'F' THEN  'FLOAT'
                  WHEN 'HM' THEN 'INTERVAL HOUR TO MINUTE'
                  WHEN 'HR' THEN 'INTERVAL HOUR'
                  WHEN 'HS' THEN 'INTERVAL HOUR TO SECOND'
                  WHEN 'I1' THEN 'BYTEINT'
                  WHEN 'I2' THEN 'SMALLINT'
                  WHEN 'I8' THEN 'BIGINT'
                  WHEN 'I' THEN  'INTEGER'
                  WHEN 'MI' THEN 'INTERVAL MINUTE'
                  WHEN 'MO' THEN 'INTERVAL MONTH'
                  WHEN 'MS' THEN 'INTERVAL MINUTE TO SECOND'
                  WHEN 'N' THEN 'NUMBER'
                  WHEN 'PD' THEN 'PERIOD(DATE)'
                  WHEN 'PM' THEN 'PERIOD(TIMESTAMP WITH TIME ZONE)'
                  WHEN 'PS' THEN 'PERIOD(TIMESTAMP)'
                  WHEN 'PT' THEN 'PERIOD(TIME)'
                  WHEN 'PZ' THEN 'PERIOD(TIME WITH TIME ZONE)'
                  WHEN 'SC' THEN 'INTERVAL SECOND'
                  WHEN 'SZ' THEN 'TIMESTAMP WITH TIME ZONE'
                  WHEN 'TS' THEN 'TIMESTAMP'
                  WHEN 'TZ' THEN 'TIME WITH TIME ZONE'
                  WHEN 'UT' THEN 'UDT'
                  WHEN 'YM' THEN 'INTERVAL YEAR TO MONTH'
                  WHEN 'YR' THEN 'INTERVAL YEAR'
                  WHEN 'AN' THEN 'UDT'
                  WHEN 'XM' THEN 'XML'
                  WHEN 'JN' THEN 'JSON'
                  WHEN 'DT' THEN 'DATASET'
                  WHEN '??' THEN 'STGEOMETRY''ANY_TYPE'
                  END as CType
              from DBC.ColumnsVX where upper(tableName) like upper(?) and upper(DatabaseName) like upper(?)
          """
          rows = cur.execute(query, [obj_name, database_name])
          data = rows_to_json(cur.description, rows.fetchall())
          metadata = {
              "tool_name": "base_columnDescription",
              "database": database_name,
              "object": obj_name,
              "column_count": len(data)
          }
          logger.debug(f"Tool: handle_base_columnDescription: metadata: {metadata}")
          return create_response(data, metadata)

• src/teradata_mcp_server/app.py:270-281 (registration)

  Dynamic registration code that scans loaded modules for functions starting with 'handle_', derives the tool name by stripping the 'handle_' prefix (e.g., 'handle_base_columnDescription' -> 'base_columnDescription'), wraps the handler with connection injection and QueryBand support, and registers it as an MCP tool using FastMCP's mcp.tool decorator.

  module_loader = td.initialize_module_loader(config)
  if module_loader:
      all_functions = module_loader.get_all_functions()
      for name, func in all_functions.items():
          if not (inspect.isfunction(func) and name.startswith("handle_")):
              continue
          tool_name = name[len("handle_"):]
          if not any(re.match(p, tool_name) for p in config.get('tool', [])):
              continue
          wrapped = make_tool_wrapper(func)
          mcp.tool(name=tool_name, description=wrapped.__doc__)(wrapped)
          logger.info(f"Created tool: {tool_name}")