diff --git a/docs/docs/integrations/vectorstores/matchingengine.ipynb b/docs/docs/integrations/vectorstores/google_vertex_ai_vector_search.ipynb
similarity index 100%
rename from docs/docs/integrations/vectorstores/matchingengine.ipynb
rename to docs/docs/integrations/vectorstores/google_vertex_ai_vector_search.ipynb
diff --git a/docs/vercel.json b/docs/vercel.json
index c7de606721f..025c56cdb69 100644
--- a/docs/vercel.json
+++ b/docs/vercel.json
@@ -504,6 +504,10 @@
       "source": "/docs/integrations/vectorstores/async_faiss",
       "destination": "/docs/integrations/vectorstores/faiss_async"
     },
+    {
+      "source": "/docs/integrations/vectorstores/matchingengine",
+      "destination": "/docs/integrations/vectorstores/google_vertex_ai_vector_search"
+    },
     {
       "source": "/docs/integrations/cerebriumai",
       "destination": "/docs/integrations/providers/cerebriumai"
diff --git a/libs/langchain/langchain/vectorstores/matching_engine.py b/libs/langchain/langchain/vectorstores/matching_engine.py
index 161e41bd5ec..a480580a760 100644
--- a/libs/langchain/langchain/vectorstores/matching_engine.py
+++ b/libs/langchain/langchain/vectorstores/matching_engine.py
@@ -26,7 +26,7 @@ logger = logging.getLogger()
 
 
 class MatchingEngine(VectorStore):
-    """`Google Vertex AI Matching Engine` vector store.
+    """`Google Vertex AI Vector Search` (previously Matching Engine) vector store.
 
     While the embeddings are stored in the Matching Engine, the embedded
     documents will be stored in GCS.
@@ -34,7 +34,7 @@ class MatchingEngine(VectorStore):
     An existing Index and corresponding Endpoint are preconditions for
     using this module.
 
-    See usage in docs/modules/indexes/vectorstores/examples/matchingengine.ipynb
+    See usage in docs/integrations/vectorstores/google_vertex_ai_vector_search.ipynb
 
     Note that this implementation is mostly meant for reading if you are
     planning to do a real time implementation. While reading is a real time
@@ -50,7 +50,8 @@ class MatchingEngine(VectorStore):
         gcs_bucket_name: str,
         credentials: Optional[Credentials] = None,
     ):
-        """Vertex Matching Engine implementation of the vector store.
+        """Google Vertex AI Vector Search (previously Matching Engine)
+         implementation of the vector store.
 
         While the embeddings are stored in the Matching Engine, the embedded
         documents will be stored in GCS.
@@ -59,7 +60,7 @@ class MatchingEngine(VectorStore):
         using this module.
 
         See usage in
-        docs/modules/indexes/vectorstores/examples/matchingengine.ipynb.
+        docs/integrations/vectorstores/google_vertex_ai_vector_search.ipynb.
 
         Note that this implementation is mostly meant for reading if you are
         planning to do a real time implementation. While reading is a real time