@@ -1893,6 +1893,24 @@ def _parse_node(self, node_data: dict[str, Any]) -> dict[str, Any]:
                 node["sources"][idx] = json.loads(node["sources"][idx])
         return {"id": node.pop("id"), "memory": node.pop("memory", ""), "metadata": node}
 
+    def _delete_vectors_for_deleted_nodes(self, node_ids: list[str]) -> None:
+        """Purge the embeddings of just-deleted graph nodes from the vector store.
+
+        Deleting a graph node alone leaves its vector behind, and vector search is
+        what retrieval reads first, so the deleted memory stays retrievable. The
+        vector store is an external dependency, so a failure here is logged rather
+        than raised: the graph deletion is already committed and must not be
+        reported as failed.
+        """
+        vec_db = getattr(self, "vec_db", None)
+        if not node_ids or vec_db is None:
+            return
+        try:
+            vec_db.delete(node_ids)
+            logger.info("[delete_node_by_prams] Deleted %d vectors from VecDB", len(node_ids))
+        except Exception as e:
+            logger.warning("[delete_node_by_prams] Failed to delete vectors from VecDB: %s", e)
+
     def delete_node_by_prams(
         self,
         writable_cube_ids: list[str] | None = None,
@@ -1998,9 +2016,16 @@ def delete_node_by_prams(
         delete_query = f"MATCH (n:Memory) WHERE {final_where} DETACH DELETE n"
         logger.info(f"[delete_node_by_prams] delete_query: {delete_query}")
 
+        # Collect the IDs in the same transaction, before the nodes are gone, so their
+        # embedding vectors can be purged from the vector store afterwards.
+        id_collect_query = f"MATCH (n:Memory) WHERE {final_where} RETURN n.id AS id"
+
         deleted_count = 0
+        deleted_ids: list[str] = []
         try:
             with self.driver.session(database=self.db_name) as session:
+                deleted_ids = [record["id"] for record in session.run(id_collect_query, **params)]
+
                 # Execute delete query
                 result = session.run(delete_query, **params)
                 # Consume the result to ensure deletion completes and get the summary
@@ -2016,6 +2041,7 @@ def delete_node_by_prams(
             logger.error(f"[delete_node_by_prams] Failed to delete nodes: {e}", exc_info=True)
             raise
 
+        self._delete_vectors_for_deleted_nodes(deleted_ids)
         logger.info(f"[delete_node_by_prams] Successfully deleted {deleted_count} nodes")
         return deleted_count
 
 
@@ -1038,10 +1038,11 @@ def delete_node_by_prams(
             f"[delete_node_by_prams] Deleting nodes - memory_ids: {memory_ids}, file_ids: {file_ids}, filter: {filter}"
         )
 
-        # First count matching nodes to get accurate count
-        count_query = f"MATCH (n:Memory) WHERE {ids_where} RETURN count(n) AS node_count"
-        logger.info(f"[delete_node_by_prams] count_query: {count_query}")
-        print(f"[delete_node_by_prams] count_query: {count_query}")
+        # First collect the matching node IDs so their embedding vectors can be
+        # purged from the vector store after the graph deletion.
+        id_collect_query = f"MATCH (n:Memory) WHERE {ids_where} RETURN n.id AS id"
+        logger.info(f"[delete_node_by_prams] id_collect_query: {id_collect_query}")
+        print(f"[delete_node_by_prams] id_collect_query: {id_collect_query}")
 
         # Then delete nodes
         delete_query = f"MATCH (n:Memory) WHERE {ids_where} DETACH DELETE n"
@@ -1050,24 +1051,22 @@ def delete_node_by_prams(
         print(f"[delete_node_by_prams] params: {params}")
 
         deleted_count = 0
+        deleted_ids: list[str] = []
         try:
             with self.driver.session(database=self.db_name) as session:
-                # Count nodes before deletion
-                count_result = session.run(count_query, **params)
-                count_record = count_result.single()
-                expected_count = 0
-                if count_record:
-                    expected_count = count_record["node_count"] or 0
+                # Collect the IDs before deletion
+                deleted_ids = [record["id"] for record in session.run(id_collect_query, **params)]
+                # Use the count from before deletion as the actual deleted count
+                deleted_count = len(deleted_ids)
 
                 # Delete nodes
                 session.run(delete_query, **params)
-                # Use the count from before deletion as the actual deleted count
-                deleted_count = expected_count
 
         except Exception as e:
             logger.error(f"[delete_node_by_prams] Failed to delete nodes: {e}", exc_info=True)
             raise
 
+        self._delete_vectors_for_deleted_nodes(deleted_ids)
         logger.info(f"[delete_node_by_prams] Successfully deleted {deleted_count} nodes")
         return deleted_count
 
 
@@ -0,0 +1,224 @@
+"""
+Regression test for issue #2331: deleting memories must also purge their vectors.
+
+`Neo4jCommunityGraphDB.delete_node_by_prams` removed the Neo4j nodes but never
+removed the matching embeddings from `vec_db`, so a deleted memory stayed
+retrievable through vector search while the delete API still answered "success".
+`clear()` and `delete_node_by_mem_cube_id()` already purged `vec_db`;
+`delete_node_by_prams` simply omitted that step.
+
+The Neo4j driver and the vector store are both faked, so these tests need no
+Neo4j, no Qdrant, and no network.
+"""
+
+from types import SimpleNamespace
+from unittest.mock import MagicMock, patch
+
+import pytest
+
+from memos.configs.graph_db import Neo4jCommunityGraphDBConfig, Neo4jGraphDBConfig
+
+
+class _FakeNeo4jSession:
+    """Minimal stand-in for a neo4j session that tracks a set of live node ids."""
+
+    def __init__(self, live_ids: set[str], issued_queries: list[str]):
+        self.live_ids = live_ids
+        self.issued_queries = issued_queries
+
+    def run(self, query, params=None, **kwargs):
+        self.issued_queries.append(query)
+        params = params or kwargs
+        ids = params.get("memory_ids") or params.get("filter_ids")
+        matched = sorted(i for i in self.live_ids if ids is None or i in ids)
+        if "count(n) AS node_count" in query:
+            return _FakeResult([{"node_count": len(matched)}])
+        if "DETACH DELETE" in query:
+            self.live_ids.difference_update(matched)
+            return _FakeResult([], deleted=len(matched))
+        if "RETURN n.id AS id" in query:
+            return _FakeResult([{"id": i} for i in matched])
+        return _FakeResult([])
+
+    def __enter__(self):
+        return self
+
+    def __exit__(self, *exc):
+        return False
+
+
+class _FakeResult:
+    """Minimal stand-in for a neo4j Result (iterable, plus .single()/.consume())."""
+
+    def __init__(self, records, deleted: int = 0):
+        self._records = records
+        self._deleted = deleted
+
+    def __iter__(self):
+        return iter(self._records)
+
+    def single(self):
+        return self._records[0] if self._records else None
+
+    def consume(self):
+        return SimpleNamespace(counters=SimpleNamespace(nodes_deleted=self._deleted))
+
+
+def _base_config_kwargs() -> dict:
+    return {
+        "uri": "bolt://localhost:7687",
+        "user": "neo4j",
+        "password": "test",
+        "db_name": "test_memory_db",
+        "auto_create": False,
+        "use_multi_db": False,
+        "user_name": "alice",
+        "embedding_dimension": 3,
+    }
+
+
+@pytest.fixture
+def community_config():
+    """`neo4j-community` is the backend that owns a `vec_db` mirror."""
+    return Neo4jCommunityGraphDBConfig(
+        **_base_config_kwargs(),
+        vec_config={
+            "backend": "qdrant",
+            "config": {
+                "collection_name": "test_vectors",
+                "path": "/tmp/memos_test_vectors",
+            },
+        },
+    )
+
+
+@pytest.fixture
+def enterprise_config():
+    """`neo4j` has no `vec_db`; it searches the native vector index instead."""
+    return Neo4jGraphDBConfig(**_base_config_kwargs())
+
+
+@pytest.fixture
+def community_db(community_config):
+    """Community backend with a faked driver and a faked vector store."""
+    from memos.graph_dbs.neo4j_community import Neo4jCommunityGraphDB
+
+    live_ids = {"mem-1", "mem-2", "mem-3"}
+    issued_queries: list[str] = []
+
+    with patch("neo4j.GraphDatabase") as mock_gd:
+        mock_gd.driver.return_value = MagicMock()
+        with patch("memos.graph_dbs.neo4j_community.VecDBFactory.from_config") as mock_factory:
+            mock_factory.return_value = MagicMock()
+            db = Neo4jCommunityGraphDB(community_config)
+
+    db.driver = MagicMock()
+    db.driver.session.side_effect = lambda **kwargs: _FakeNeo4jSession(live_ids, issued_queries)
+
+    vector_ids = set(live_ids)
+    db.vec_db = MagicMock()
+    db.vec_db.delete.side_effect = lambda ids: [vector_ids.discard(i) for i in ids]
+
+    db.live_ids = live_ids
+    db.vector_ids = vector_ids
+    db.issued_queries = issued_queries
+    return db
+
+
+class TestCommunityDeletePurgesVectors:
+    """Regression: the community backend deletes vectors together with nodes."""
+
+    def test_delete_by_memory_ids_purges_vectors(self, community_db):
+        deleted = community_db.delete_node_by_prams(memory_ids=["mem-1", "mem-2"])
+
+        assert deleted == 2
+        assert community_db.live_ids == {"mem-3"}
+        assert community_db.vector_ids == {"mem-3"}, "vectors of deleted nodes must not survive"
+        assert community_db.vec_db.delete.call_count == 1
+        assert sorted(community_db.vec_db.delete.call_args[0][0]) == ["mem-1", "mem-2"]
+
+    def test_graph_deletion_and_return_value_unchanged(self, community_db):
+        """The fix must not change which nodes the graph store deletes."""
+        deleted = community_db.delete_node_by_prams(memory_ids=["mem-3"])
+
+        assert deleted == 1
+        assert community_db.live_ids == {"mem-1", "mem-2"}
+        assert community_db.vector_ids == {"mem-1", "mem-2"}
+        assert any("DETACH DELETE" in q for q in community_db.issued_queries)
+
+    def test_vec_db_failure_does_not_mask_successful_delete(self, community_db):
+        """A vector store outage must not turn a committed delete into a failure."""
+        community_db.vec_db.delete.side_effect = RuntimeError("qdrant unreachable")
+
+        deleted = community_db.delete_node_by_prams(memory_ids=["mem-1"])
+
+        assert deleted == 1
+        assert community_db.live_ids == {"mem-2", "mem-3"}
+
+    def test_delete_by_filter_purges_vectors(self, community_db):
+        """Deleting by metadata filter must purge vectors too."""
+        community_db.get_by_metadata = MagicMock(return_value=["mem-1", "mem-3"])
+
+        deleted = community_db.delete_node_by_prams(filter={"user_id": "u_1"})
+
+        assert deleted == 2
+        assert community_db.live_ids == {"mem-2"}
+        assert community_db.vector_ids == {"mem-2"}
+        assert sorted(community_db.vec_db.delete.call_args[0][0]) == ["mem-1", "mem-3"]
+
+    def test_no_match_does_not_touch_vec_db(self, community_db):
+        """An empty match set must not issue a vector delete call."""
+        deleted = community_db.delete_node_by_prams(memory_ids=["does-not-exist"])
+
+        assert deleted == 0
+        assert community_db.live_ids == {"mem-1", "mem-2", "mem-3"}
+        assert community_db.vector_ids == {"mem-1", "mem-2", "mem-3"}
+        community_db.vec_db.delete.assert_not_called()
+
+    def test_clear_still_purges_all_vectors(self, community_db):
+        """The neighbouring `clear()` path keeps working after the refactor."""
+        community_db.vec_db.get_by_filter.return_value = [
+            SimpleNamespace(id="mem-1"),
+            SimpleNamespace(id="mem-2"),
+        ]
+
+        community_db.clear(user_name="alice")
+
+        community_db.vec_db.get_by_filter.assert_called_once_with({"user_name": "alice"})
+        community_db.vec_db.delete.assert_called_once_with(["mem-1", "mem-2"])
+        assert community_db.live_ids == set()
+        assert any("DETACH DELETE" in q for q in community_db.issued_queries)
+
+
+class TestBackendWithoutVecDB:
+    """`neo4j` sets up no `vec_db`, so the vector purge must degrade to a no-op."""
+
+    @pytest.fixture
+    def enterprise_db(self, enterprise_config):
+        from memos.graph_dbs.neo4j import Neo4jGraphDB
+
+        live_ids = {"mem-1", "mem-2", "mem-3"}
+        issued_queries: list[str] = []
+
+        with patch("neo4j.GraphDatabase") as mock_gd:
+            mock_gd.driver.return_value = MagicMock()
+            db = Neo4jGraphDB(enterprise_config)
+
+        db.driver = MagicMock()
+        db.driver.session.side_effect = lambda **kwargs: _FakeNeo4jSession(live_ids, issued_queries)
+        db.live_ids = live_ids
+        db.issued_queries = issued_queries
+        return db
+
+    def test_delete_without_vec_db_succeeds(self, enterprise_db):
+        deleted = enterprise_db.delete_node_by_prams(memory_ids=["mem-1", "mem-2"])
+
+        assert deleted == 2
+        assert enterprise_db.live_ids == {"mem-3"}
+        assert any("DETACH DELETE" in q for q in enterprise_db.issued_queries)
+
+    def test_no_match_without_vec_db(self, enterprise_db):
+        deleted = enterprise_db.delete_node_by_prams(memory_ids=["does-not-exist"])
+
+        assert deleted == 0
+        assert enterprise_db.live_ids == {"mem-1", "mem-2", "mem-3"}