diff --git a/CHANGELOG.md b/CHANGELOG.md
index 5d44d108b..aae14f431 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -13,6 +13,13 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
   `DailyTransport.stop_transcription()` to be able to start and stop Daily
   transcription dynamically (maybe with different settings).
 
+### Fixed
+
+- In `AWSBedrockLLMService`, worked around a possible bug in AWS Bedrock where
+  a `toolConfig` is required if there has been previous tool use in the
+  messages array. This workaround includes a no_op factory function call is
+  used to satisfy the requirement.
+
 ## [0.0.68] - 2025-05-28
 
 ### Added
diff --git a/src/pipecat/services/aws/llm.py b/src/pipecat/services/aws/llm.py
index 9ec617678..a90620b20 100644
--- a/src/pipecat/services/aws/llm.py
+++ b/src/pipecat/services/aws/llm.py
@@ -606,6 +606,21 @@ class AWSBedrockLLMService(LLMService):
         assistant = AWSBedrockAssistantContextAggregator(context, params=assistant_params)
         return AWSBedrockContextAggregatorPair(_user=user, _assistant=assistant)
 
+    def _create_no_op_tool(self):
+        """Create a no-operation tool for AWS Bedrock when tool content exists but no tools are defined.
+
+        This is required because AWS Bedrock doesn't allow empty tool configurations after tools were
+        previously set. Other LLM vendors allow NOT_GIVEN or empty tool configurations,
+        but AWS Bedrock requires at least one tool to be defined.
+        """
+        return {
+            "toolSpec": {
+                "name": "no_operation",
+                "description": "Internal placeholder function. Do not call this function.",
+                "inputSchema": {"json": {"type": "object", "properties": {}, "required": []}},
+            }
+        }
+
     @traced_llm
     async def _process_context(self, context: AWSBedrockLLMContext):
         # Usage tracking
@@ -616,6 +631,8 @@ class AWSBedrockLLMService(LLMService):
         cache_creation_input_tokens = 0
         use_completion_tokens_estimate = False
 
+        using_noop_tool = False
+
         try:
             await self.push_frame(LLMFullResponseStartFrame())
             await self.start_processing_metrics()
@@ -640,12 +657,28 @@ class AWSBedrockLLMService(LLMService):
             # Add system message
             request_params["system"] = context.system
 
-            # Add tools if present
-            if context.tools:
-                tool_config = {"tools": context.tools}
+            # Check if messages contain tool use or tool result content blocks
+            has_tool_content = False
+            for message in context.messages:
+                if isinstance(message.get("content"), list):
+                    for content_item in message["content"]:
+                        if "toolUse" in content_item or "toolResult" in content_item:
+                            has_tool_content = True
+                            break
+                if has_tool_content:
+                    break
 
-                # Add tool_choice if specified
-                if context.tool_choice:
+            # Handle tools: use current tools, or no-op if tool content exists but no current tools
+            tools = context.tools or []
+            if has_tool_content and not tools:
+                tools = [self._create_no_op_tool()]
+                using_noop_tool = True
+
+            if tools:
+                tool_config = {"tools": tools}
+
+                # Only add tool_choice if we have real tools (not just no-op)
+                if not using_noop_tool and context.tool_choice:
                     if context.tool_choice == "auto":
                         tool_config["toolChoice"] = {"auto": {}}
                     elif context.tool_choice == "none":
@@ -704,12 +737,17 @@ class AWSBedrockLLMService(LLMService):
                     if event["messageStop"]["stopReason"] == "tool_use" and tool_use_block:
                         try:
                             arguments = json.loads(json_accumulator) if json_accumulator else {}
-                            await self.call_function(
-                                context=context,
-                                tool_call_id=tool_use_block["id"],
-                                function_name=tool_use_block["name"],
-                                arguments=arguments,
-                            )
+
+                            # Only call function if it's not the no_operation tool
+                            if not using_noop_tool:
+                                await self.call_function(
+                                    context=context,
+                                    tool_call_id=tool_use_block["id"],
+                                    function_name=tool_use_block["name"],
+                                    arguments=arguments,
+                                )
+                            else:
+                                logger.debug("Ignoring no_operation tool call")
                         except json.JSONDecodeError:
                             logger.error(f"Failed to parse tool arguments: {json_accumulator}")