# MCP:L5 fixes in mcp\_chatbot.py to run it locally

**URL:** <https://community.deeplearning.ai/t/mcp-l5-fixes-in-mcp-chatbot-py-to-run-it-locally/889719>\
**Category:** MCP: Build Rich-Context AI Apps with Anthropic\
**Tags:** ai-discussions\
**Created:** [March 2, 2026, 6:02pm UTC](https://community.deeplearning.ai/t/mcp-l5-fixes-in-mcp-chatbot-py-to-run-it-locally/889719 "2026-03-02T18:02:48Z")\
**Posts on this page:** 1\
**Showing post:** 6

<div class="post-metadata">

**Author:** ![lesly.zerna](https://sea1.discourse-cdn.com/dlai/user_avatar/community.deeplearning.ai/lesly.zerna/32/47465_2.png) [@lesly.zerna](https://community.deeplearning.ai/u/lesly.zerna)\
**Post date:** [March 3, 2026, 6:39pm UTC](https://community.deeplearning.ai/t/mcp-l5-fixes-in-mcp-chatbot-py-to-run-it-locally/889719/6 "2026-03-03T18:39:15Z")

</div>

Interesting! I see, the `L5/mcp_project/mcp_chatbot.py` and it looks like the problem is in the `tool_use` handling block. Try using this instead…

```python
async def process_query(self, query):       
      messages = [{‘role’: ‘user’, ‘content’: query}]       
      response = self.anthropic.messages.create(                           
            max_tokens=2024,                       
            model = ‘claude-sonnet-4-6’,
            tools=self.available_tools,
            messages=messages
      )

process_query = True
while process_query:
    assistant_content = []
    tool_results = [] # collect ALL tool results first
    has_tool_use = False

    for content in response.content:
        if content.type == 'text':
            print(content.text)
            assistant_content.append(content)
        elif content.type == 'tool_use':
            has_tool_use = True
            assistant_content.append(content)
            tool_name = content.name
            tool_args = content.input
            tool_id = content.id

            print(f"Calling tool {tool_name} with args {tool_args}")
            result = await self.session.call_tool(tool_name, arguments=tool_args)

            tool_results.append({ # collect, don't send yet
                "type": "tool_result",
                "tool_use_id": tool_id,
                "content": result.content
            })

    if has_tool_use:
        # Now send assistant message + ALL tool results together
        messages.append({'role': 'assistant', 'content': assistant_content})
        messages.append({'role': 'user', 'content': tool_results})

        response = self.anthropic.messages.create(
            max_tokens=2024,
            model='claude-3-7-sonnet-20250219',
            tools=self.available_tools,
            messages=messages
        )
    else:
        process_query = False # no tools called, we're done
...

```

Let us know if that helps!

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