diff --git a/libs/knowledge-store/ragstack_knowledge_store/graph_store.py b/libs/knowledge-store/ragstack_knowledge_store/graph_store.py
index 02110a62e..0e391214c 100644
--- a/libs/knowledge-store/ragstack_knowledge_store/graph_store.py
+++ b/libs/knowledge-store/ragstack_knowledge_store/graph_store.py
@@ -367,6 +367,7 @@ def mmr_traversal_search(
         lambda_mult: float = 0.5,
         score_threshold: float = float("-inf"),
         metadata_filter: dict[str, Any] = {},  # noqa: B006
+        tag_filter: set[tuple[str, str]] = {},
     ) -> Iterable[Node]:
         """Retrieve documents from this graph store using MMR-traversal.
 
@@ -398,6 +399,7 @@ def mmr_traversal_search(
             score_threshold: Only documents with a score greater than or equal
                 this threshold will be chosen. Defaults to -infinity.
             metadata_filter: Optional metadata to filter the results.
+            tag_filter: Optional tags to filter graph edges to be traversed.
         """
         query_embedding = self._embedding.embed_query(query)
         helper = MmrHelper(
@@ -444,9 +446,14 @@ def fetch_neighborhood(neighborhood: Sequence[str]) -> None:
             new_candidates = {}
             for adjacent in adjacents:
                 if adjacent.target_content_id not in outgoing_tags:
-                    outgoing_tags[adjacent.target_content_id] = (
-                        adjacent.target_link_to_tags
-                    )
+                    if len(tag_filter) == 0:
+                        outgoing_tags[adjacent.target_content_id] = (
+                            adjacent.target_link_to_tags
+                        )
+                    else:
+                        outgoing_tags[adjacent.target_content_id] = (
+                            tag_filter.intersection(adjacent.target_link_to_tags)
+                        )
 
                     new_candidates[adjacent.target_content_id] = (
                         adjacent.target_text_embedding
@@ -474,7 +481,12 @@ def fetch_initial_candidates() -> None:
             for row in fetched:
                 if row.content_id not in outgoing_tags:
                     candidates[row.content_id] = row.text_embedding
-                    outgoing_tags[row.content_id] = set(row.link_to_tags or [])
+                    if len(tag_filter) == 0:
+                        outgoing_tags[row.content_id] = set(row.link_to_tags or [])
+                    else:
+                        outgoing_tags[row.content_id] = tag_filter.intersection(
+                            set(row.link_to_tags or [])
+                        )
             helper.add_candidates(candidates)
 
         if initial_roots:
@@ -522,9 +534,14 @@ def fetch_initial_candidates() -> None:
                 new_candidates = {}
                 for adjacent in adjacents:
                     if adjacent.target_content_id not in outgoing_tags:
-                        outgoing_tags[adjacent.target_content_id] = (
-                            adjacent.target_link_to_tags
-                        )
+                        if len(tag_filter) == 0:
+                            outgoing_tags[adjacent.target_content_id] = (
+                                adjacent.target_link_to_tags
+                            )
+                        else:
+                            outgoing_tags[adjacent.target_content_id] = (
+                                tag_filter.intersection(adjacent.target_link_to_tags)
+                            )
                         new_candidates[adjacent.target_content_id] = (
                             adjacent.target_text_embedding
                         )
@@ -553,6 +570,7 @@ def traversal_search(
         k: int = 4,
         depth: int = 1,
         metadata_filter: dict[str, Any] = {},  # noqa: B006
+        tag_filter: set[tuple[str, str]] = {},
     ) -> Iterable[Node]:
         """Retrieve documents from this knowledge store.
 
@@ -566,6 +584,7 @@ def traversal_search(
                 Defaults to 4.
             depth: The maximum depth of edges to traverse. Defaults to 1.
             metadata_filter: Optional metadata to filter the results.
+            tag_filter: Optional tags to filter graph edges to be traversed.
 
         Returns:
             Collection of retrieved documents.
@@ -630,7 +649,11 @@ def visit_nodes(d: int, nodes: Sequence[Any]) -> None:
                                     # given depth, so we don't fetch it again
                                     # (unless we find it an earlier depth)
                                     visited_tags[(kind, value)] = d
-                                    outgoing_tags.add((kind, value))
+                                    if (
+                                        len(tag_filter) == 0
+                                        or (kind, value) in tag_filter
+                                    ):
+                                        outgoing_tags.add((kind, value))
 
                 if outgoing_tags:
                     # If there are new tags to visit at the next depth, query for the
diff --git a/libs/knowledge-store/tests/integration_tests/test_graph_store.py b/libs/knowledge-store/tests/integration_tests/test_graph_store.py
index 17d5a7a77..6bb8ba506 100644
--- a/libs/knowledge-store/tests/integration_tests/test_graph_store.py
+++ b/libs/knowledge-store/tests/integration_tests/test_graph_store.py
@@ -211,6 +211,16 @@ def test_mmr_traversal(
     results = gs.mmr_traversal_search("0.0", fetch_k=2, k=4, initial_roots=["v0"])
     assert _result_ids(results) == ["v1", "v3", "v2"]
 
+    results = gs.mmr_traversal_search(
+        "0.0", k=2, fetch_k=2, tag_filter={("explicit", "link")}
+    )
+    assert _result_ids(results) == ["v0", "v2"]
+
+    results = gs.mmr_traversal_search(
+        "0.0", k=2, fetch_k=2, tag_filter={("no", "match")}
+    )
+    assert _result_ids(results) == []
+
 
 def test_write_retrieve_keywords(
     graph_store_factory: Callable[[MetadataIndexingType], GraphStore],
@@ -282,6 +292,14 @@ def test_write_retrieve_keywords(
     results = gs.traversal_search("Earth", k=1, depth=1)
     assert set(_result_ids(results)) == {"doc2", "doc1", "greetings"}
 
+    results = gs.traversal_search(
+        "Earth", k=1, depth=1, tag_filter={("parent", "parent")}
+    )
+    assert set(_result_ids(results)) == {"doc2", "greetings"}
+
+    results = gs.traversal_search("Earth", k=1, depth=1, tag_filter={("no", "match")})
+    assert _result_ids(results) == []
+
 
 def test_metadata(
     graph_store_factory: Callable[[MetadataIndexingType], GraphStore],