diff --git a/src/memos/memories/textual/tree_text_memory/organize/manager.py b/src/memos/memories/textual/tree_text_memory/organize/manager.py
index 06a8a638d..0561d178e 100644
--- a/src/memos/memories/textual/tree_text_memory/organize/manager.py
+++ b/src/memos/memories/textual/tree_text_memory/organize/manager.py
@@ -134,10 +134,18 @@ def _add_memories_parallel(
         return added_ids
 
     def _add_memories_batch(
-        self, memories: list[TextualMemoryItem], user_name: str | None = None
+        self, memories: list[TextualMemoryItem], user_name: str | None = None, batch_size: int = 10
     ) -> list[str]:
         """
         Add memories using batch database operations (more efficient for large batches).
+
+        Args:
+            memories: List of memory items to add.
+            user_name: Optional user name for the memories.
+            batch_size: Number of nodes to insert per batch.
+
+        Returns:
+            List of added graph memory node IDs.
         """
         if not memories:
             return []
@@ -150,7 +158,6 @@ def _add_memories_batch(
         for memory in memories:
             working_id = str(uuid.uuid4())
 
-            # Prepare WorkingMemory node (skip for ToolSchemaMemory and ToolTrajectoryMemory)
             if memory.metadata.memory_type not in ("ToolSchemaMemory", "ToolTrajectoryMemory"):
                 working_metadata = memory.metadata.model_copy(
                     update={"memory_type": "WorkingMemory"}
@@ -163,8 +170,6 @@ def _add_memories_batch(
                         "metadata": working_metadata,
                     }
                 )
-
-            # Prepare graph memory node (LongTermMemory/UserMemory/ToolSchemaMemory/ToolTrajectoryMemory)
             if memory.metadata.memory_type in (
                 "LongTermMemory",
                 "UserMemory",
@@ -194,20 +199,26 @@ def _add_memories_batch(
                 graph_node_ids.append(graph_node_id)
                 added_ids.append(graph_node_id)
 
-        # Batch insert nodes
-        if working_nodes:
+        for i in range(0, len(working_nodes), batch_size):
+            batch = working_nodes[i : i + batch_size]
             try:
-                self.graph_store.add_nodes_batch(working_nodes, user_name=user_name)
+                self.graph_store.add_nodes_batch(batch, user_name=user_name)
             except Exception as e:
-                logger.exception("Batch add WorkingMemory nodes error: ", exc_info=e)
+                logger.exception(
+                    f"Batch add WorkingMemory nodes error (batch {i // batch_size + 1}): ",
+                    exc_info=e,
+                )
 
-        if graph_nodes:
+        for i in range(0, len(graph_nodes), batch_size):
+            batch = graph_nodes[i : i + batch_size]
             try:
-                self.graph_store.add_nodes_batch(graph_nodes, user_name=user_name)
+                self.graph_store.add_nodes_batch(batch, user_name=user_name)
             except Exception as e:
-                logger.exception("Batch add graph memory nodes error: ", exc_info=e)
+                logger.exception(
+                    f"Batch add graph memory nodes error (batch {i // batch_size + 1}): ",
+                    exc_info=e,
+                )
 
-        # Notify reorganizer (only if enabled)
         if graph_node_ids and self.is_reorganize:
             self.reorganizer.add_message(QueueMessage(op="add", after_node=graph_node_ids))