diff --git a/lightrag/api/config.py b/lightrag/api/config.py
index 92e81253..baaf9c52 100644
--- a/lightrag/api/config.py
+++ b/lightrag/api/config.py
@@ -343,6 +343,7 @@ def parse_args() -> argparse.Namespace:
     args.llm_model = get_env_value("LLM_MODEL", "mistral-nemo:latest")
     args.embedding_model = get_env_value("EMBEDDING_MODEL", "bge-m3:latest")
     args.embedding_dim = get_env_value("EMBEDDING_DIM", 1024, int)
+    args.embedding_send_dim = get_env_value("EMBEDDING_SEND_DIM", False, bool)
 
     # Inject chunk configuration
     args.chunk_size = get_env_value("CHUNK_SIZE", 1200, int)
diff --git a/lightrag/api/lightrag_server.py b/lightrag/api/lightrag_server.py
index 6da76f37..b3a439e8 100644
--- a/lightrag/api/lightrag_server.py
+++ b/lightrag/api/lightrag_server.py
@@ -709,8 +709,8 @@ def create_app(args):
         args=args,  # Pass args object for fallback option generation
     )
 
-    # Check environment variable for sending dimensions
-    embedding_send_dim = os.getenv("EMBEDDING_SEND_DIM", "false").lower() == "true"
+    # Get embedding_send_dim from centralized configuration
+    embedding_send_dim = args.embedding_send_dim
 
     # Check if the function signature has embedding_dim parameter
     # Note: Since optimized_embedding_func is an async function, inspect its signature