diff --git a/letta/adapters/simple_llm_request_adapter.py b/letta/adapters/simple_llm_request_adapter.py
index ca5c70ce..ab3f662d 100644
--- a/letta/adapters/simple_llm_request_adapter.py
+++ b/letta/adapters/simple_llm_request_adapter.py
@@ -71,10 +71,9 @@ class SimpleLLMRequestAdapter(LettaLLMRequestAdapter):
             self.content = self.reasoning_content + (self.content or [])
 
         # Extract tool call
-        if self.chat_completions_response.choices[0].message.tool_calls:
-            self.tool_call = self.chat_completions_response.choices[0].message.tool_calls[0]
-        else:
-            self.tool_call = None
+        tool_calls = self.chat_completions_response.choices[0].message.tool_calls or []
+        self.tool_calls = list(tool_calls)
+        self.tool_call = self.tool_calls[0] if self.tool_calls else None
 
         # Extract usage statistics
         self.usage.step_count = 1
diff --git a/letta/llm_api/anthropic_client.py b/letta/llm_api/anthropic_client.py
index b1811cf4..feadb37a 100644
--- a/letta/llm_api/anthropic_client.py
+++ b/letta/llm_api/anthropic_client.py
@@ -575,7 +575,7 @@ class AnthropicClient(LLMClientBase):
         reasoning_content = None
         reasoning_content_signature = None
         redacted_reasoning_content = None
-        tool_calls = None
+        tool_calls: list[ToolCall] = []
 
         if len(response.content) > 0:
             for content_part in response.content:
@@ -594,7 +594,7 @@ class AnthropicClient(LLMClientBase):
                             arguments = str(tool_input["function"]["arguments"])
                     else:
                         arguments = json.dumps(tool_input, indent=2)
-                    tool_calls = [
+                    tool_calls.append(
                         ToolCall(
                             id=content_part.id,
                             type="function",
@@ -603,7 +603,7 @@ class AnthropicClient(LLMClientBase):
                                 arguments=arguments,
                             ),
                         )
-                    ]
+                    )
                 if content_part.type == "thinking":
                     reasoning_content = content_part.thinking
                     reasoning_content_signature = content_part.signature
@@ -623,7 +623,7 @@ class AnthropicClient(LLMClientBase):
                 reasoning_content=reasoning_content,
                 reasoning_content_signature=reasoning_content_signature,
                 redacted_reasoning_content=redacted_reasoning_content,
-                tool_calls=tool_calls,
+                tool_calls=tool_calls or None,
             ),
         )
 
diff --git a/tests/integration_test_send_message_v2.py b/tests/integration_test_send_message_v2.py
index c83a9f5e..e2de6ed1 100644
--- a/tests/integration_test_send_message_v2.py
+++ b/tests/integration_test_send_message_v2.py
@@ -522,9 +522,9 @@ async def test_greeting(
     TESTED_LLM_CONFIGS,
     ids=[c.model for c in TESTED_LLM_CONFIGS],
 )
-@pytest.mark.parametrize("send_type", ["stream_tokens"])  # ["step", "stream_steps", "stream_tokens", "stream_tokens_background"])
+@pytest.mark.parametrize("send_type", ["step", "stream_tokens"])  # ["step", "stream_steps", "stream_tokens", "stream_tokens_background"])
 @pytest.mark.asyncio(loop_scope="function")
-async def test_parallel_tool_call_anthropic_streaming(
+async def test_parallel_tool_call_anthropic(
     disable_e2b_api_key: Any,
     client: AsyncLetta,
     agent_state: AgentState,