diff --git a/integrations/langchain/src/databricks_langchain/vector_search.py b/integrations/langchain/src/databricks_langchain/vector_search.py
new file mode 100644
index 0000000..728f263
--- /dev/null
+++ b/integrations/langchain/src/databricks_langchain/vector_search.py
@@ -0,0 +1,8 @@
+from databricks_langchain.vector_search import DatabricksVectorSearch
+class VectorSearchRetrieverTool():
+    def __init__(self, *args, **kwargs):
+        vector_store = DatabricksVectorSearch(
+            endpoint=endpoint_name,
+            index_name=index_name,
+        )
+        return vector_store.as_retriever().as_tool()
diff --git a/src/databricks_ai_bridge/vector_search.py b/src/databricks_ai_bridge/vector_search.py
new file mode 100644
index 0000000..211830b
--- /dev/null
+++ b/src/databricks_ai_bridge/vector_search.py
@@ -0,0 +1,2 @@
+# Put common logic for exposing Databricks vector search as a tool here
+# for example: querying a VS endpoint, getting metadata about the index, ...