diff --git a/litellm/llms/anthropic/experimental_pass_through/messages/handler.py b/litellm/llms/anthropic/experimental_pass_through/messages/handler.py
index 5b215c1fe54..aa73ab18f90 100644
--- a/litellm/llms/anthropic/experimental_pass_through/messages/handler.py
+++ b/litellm/llms/anthropic/experimental_pass_through/messages/handler.py
@@ -24,6 +24,10 @@
 from litellm.types.router import GenericLiteLLMParams
 from litellm.utils import ProviderConfigManager, client
 
+from litellm.litellm_core_utils.prompt_templates.common_utils import (
+    DEFAULT_ASSISTANT_CONTINUE_MESSAGE,
+)
+
 from ..adapters.handler import LiteLLMMessagesToCompletionTransformationHandler
 from ..responses_adapters.handler import LiteLLMMessagesToResponsesAPIHandler
 from .utils import AnthropicMessagesRequestUtils, mock_response
@@ -49,6 +53,58 @@ def _should_route_to_responses_api(custom_llm_provider: Optional[str]) -> bool:
 #################################################
 
 
+def _sanitize_anthropic_messages(messages: List[Dict]) -> List[Dict]:
+    """
+    Sanitize messages for the /v1/messages endpoint.
+
+    The Anthropic API can return assistant messages with empty text blocks
+    alongside tool_use blocks (e.g., {"type": "text", "text": ""}). While
+    the API returns these, it rejects them when sent back in subsequent
+    requests with "text content blocks must be non-empty".
+
+    This is particularly common in multi-turn tool-use conversations (e.g.,
+    Claude Code / Agent SDK) where the model starts a text block but
+    immediately switches to a tool_use block.
+
+    The /v1/chat/completions path already handles this via
+    process_empty_text_blocks() in factory.py, but the /v1/messages path
+    was missing sanitization.
+    """
+    for i, message in enumerate(messages):
+        content = message.get("content")
+        if not isinstance(content, list):
+            continue
+
+        # Filter out empty text blocks, keeping non-empty text and other types.
+        # Use `(... or "")` to guard against None text values.
+        filtered = [
+            block
+            for block in content
+            if not (
+                isinstance(block, dict)
+                and block.get("type") == "text"
+                and not (block.get("text") or "").strip()
+            )
+        ]
+
+        # Only update if we actually removed something.
+        # Avoid mutating the caller's dicts — create a shallow copy.
+        if len(filtered) < len(content):
+            if len(filtered) > 0:
+                messages[i] = {**message, "content": filtered}
+            else:
+                # All blocks were empty text — replace with a continuation
+                # message rather than leaving empty blocks that trigger 400
+                # errors. Matches behavior of process_empty_text_blocks()
+                # in factory.py.
+                messages[i] = {
+                    **message,
+                    "content": [{"type": "text", "text": DEFAULT_ASSISTANT_CONTINUE_MESSAGE.get("content", "Please continue.")}],
+                }
+
+    return messages
+
+
 async def _execute_pre_request_hooks(
     model: str,
     messages: List[Dict],
@@ -137,6 +193,10 @@ async def anthropic_messages(
     """
     Async: Make llm api request in Anthropic /messages API spec
     """
+    # Sanitize empty text blocks from messages before processing.
+    # See: https://github.com/BerriAI/litellm/issues/22930
+    messages = _sanitize_anthropic_messages(messages)
+
     # Execute pre-request hooks to allow CustomLoggers to modify request
     request_kwargs = await _execute_pre_request_hooks(
         model=model,
diff --git a/tests/test_litellm/llms/anthropic/experimental_pass_through/messages/test_anthropic_experimental_pass_through_messages_handler.py b/tests/test_litellm/llms/anthropic/experimental_pass_through/messages/test_anthropic_experimental_pass_through_messages_handler.py
index 636e84fe796..243a06ed716 100644
--- a/tests/test_litellm/llms/anthropic/experimental_pass_through/messages/test_anthropic_experimental_pass_through_messages_handler.py
+++ b/tests/test_litellm/llms/anthropic/experimental_pass_through/messages/test_anthropic_experimental_pass_through_messages_handler.py
@@ -190,6 +190,152 @@ def test_openai_model_with_thinking_converts_to_reasoning():
         assert "thinking" not in call_kwargs, "thinking should NOT be passed directly to litellm.responses"
 
 
+class TestSanitizeAnthropicMessages:
+    """Tests for _sanitize_anthropic_messages which strips empty text blocks."""
+
+    def test_strips_empty_text_block_alongside_tool_use(self):
+        """The most common case: model returns empty text + tool_use."""
+        from litellm.llms.anthropic.experimental_pass_through.messages.handler import (
+            _sanitize_anthropic_messages,
+        )
+
+        messages = [
+            {"role": "user", "content": "Use the bash tool to list files"},
+            {
+                "role": "assistant",
+                "content": [
+                    {"type": "text", "text": ""},
+                    {"type": "tool_use", "id": "toolu_123", "name": "Bash", "input": {"cmd": "ls"}},
+                ],
+            },
+        ]
+        result = _sanitize_anthropic_messages(messages)
+        assistant = result[1]
+        assert len(assistant["content"]) == 1
+        assert assistant["content"][0]["type"] == "tool_use"
+
+    def test_strips_whitespace_only_text_block(self):
+        from litellm.llms.anthropic.experimental_pass_through.messages.handler import (
+            _sanitize_anthropic_messages,
+        )
+
+        messages = [
+            {
+                "role": "assistant",
+                "content": [
+                    {"type": "text", "text": "  \n  "},
+                    {"type": "tool_use", "id": "toolu_123", "name": "Bash", "input": {}},
+                ],
+            },
+        ]
+        result = _sanitize_anthropic_messages(messages)
+        assert len(result[0]["content"]) == 1
+        assert result[0]["content"][0]["type"] == "tool_use"
+
+    def test_preserves_non_empty_text_blocks(self):
+        from litellm.llms.anthropic.experimental_pass_through.messages.handler import (
+            _sanitize_anthropic_messages,
+        )
+
+        messages = [
+            {
+                "role": "assistant",
+                "content": [
+                    {"type": "text", "text": "I'll run that for you."},
+                    {"type": "tool_use", "id": "toolu_123", "name": "Bash", "input": {}},
+                ],
+            },
+        ]
+        result = _sanitize_anthropic_messages(messages)
+        assert len(result[0]["content"]) == 2
+
+    def test_replaces_all_empty_blocks_with_continuation(self):
+        """If ALL blocks are empty text, replace with a continuation message."""
+        from litellm.llms.anthropic.experimental_pass_through.messages.handler import (
+            _sanitize_anthropic_messages,
+        )
+        from litellm.litellm_core_utils.prompt_templates.common_utils import (
+            DEFAULT_ASSISTANT_CONTINUE_MESSAGE,
+        )
+
+        messages = [
+            {
+                "role": "assistant",
+                "content": [{"type": "text", "text": ""}],
+            },
+        ]
+        result = _sanitize_anthropic_messages(messages)
+        assert len(result[0]["content"]) == 1
+        assert result[0]["content"][0]["type"] == "text"
+        assert result[0]["content"][0]["text"] == DEFAULT_ASSISTANT_CONTINUE_MESSAGE.get("content", "Please continue.")
+
+    def test_handles_string_content(self):
+        """String content (not list) should pass through unchanged."""
+        from litellm.llms.anthropic.experimental_pass_through.messages.handler import (
+            _sanitize_anthropic_messages,
+        )
+
+        messages = [{"role": "user", "content": "Hello"}]
+        result = _sanitize_anthropic_messages(messages)
+        assert result[0]["content"] == "Hello"
+
+    def test_handles_user_messages_too(self):
+        """User messages can also have content lists with empty text blocks."""
+        from litellm.llms.anthropic.experimental_pass_through.messages.handler import (
+            _sanitize_anthropic_messages,
+        )
+
+        messages = [
+            {
+                "role": "user",
+                "content": [
+                    {"type": "text", "text": ""},
+                    {"type": "tool_result", "tool_use_id": "toolu_123", "content": "file1.txt"},
+                ],
+            },
+        ]
+        result = _sanitize_anthropic_messages(messages)
+        assert len(result[0]["content"]) == 1
+        assert result[0]["content"][0]["type"] == "tool_result"
+
+
+    def test_handles_none_text_value(self):
+        """Text blocks with None text value should be treated as empty, not crash."""
+        from litellm.llms.anthropic.experimental_pass_through.messages.handler import (
+            _sanitize_anthropic_messages,
+        )
+
+        messages = [
+            {
+                "role": "assistant",
+                "content": [
+                    {"type": "text", "text": None},
+                    {"type": "tool_use", "id": "toolu_123", "name": "Bash", "input": {}},
+                ],
+            },
+        ]
+        result = _sanitize_anthropic_messages(messages)
+        assert len(result[0]["content"]) == 1
+        assert result[0]["content"][0]["type"] == "tool_use"
+
+    def test_does_not_mutate_original_message(self):
+        """Sanitized messages should be shallow copies, not mutated originals."""
+        from litellm.llms.anthropic.experimental_pass_through.messages.handler import (
+            _sanitize_anthropic_messages,
+        )
+
+        original_content = [
+            {"type": "text", "text": ""},
+            {"type": "tool_use", "id": "toolu_123", "name": "Bash", "input": {}},
+        ]
+        messages = [{"role": "assistant", "content": original_content}]
+        result = _sanitize_anthropic_messages(messages)
+        # Original content list should be unchanged
+        assert len(original_content) == 2
+        # Result message should be a different dict
+        assert len(result[0]["content"]) == 1
+
+
 class TestThinkingParameterTransformation:
     """Core tests for thinking parameter transformation logic."""