fix: fix the system message in simple-chatbot example

[yukuanj]

In the simple-chatbot example, I have updated the system message to explicitly suppress the triple backticks fences output by the LLM. Otherwise, the triple backticks fences would prevent the tool calling.

Motivation and Context

When I executed the simple-chatbot example, I observed:

python main.py
You: What tools do you have?
2025-09-24 17:31:02,549 - INFO - HTTP Request: POST https://api.groq.com/openai/v1/chat/completions "HTTP/1.1 200 OK"
2025-09-24 17:31:02,552 - INFO - 
Assistant: I have the following tools:

1. `read_query`: Execute a SELECT query on the SQLite database
2. `write_query`: Execute an INSERT, UPDATE, or DELETE query on the SQLite database
3. `create_table`: Create a new table in the SQLite database
4. `list_tables`: List all tables in the SQLite database
5. `describe_table`: Get the schema information for a specific table
6. `append_insight`: Add a business insight to the memo
7. `puppeteer_navigate`: Navigate to a URL
8. `puppeteer_screenshot`: Take a screenshot of the current page or a specific element
9. `puppeteer_click`: Click an element on the page
10. `puppeteer_fill`: Fill out an input field
11. `puppeteer_select`: Select an element on the page with Select tag
12. `puppeteer_hover`: Hover an element on the page
13. `puppeteer_evaluate`: Execute JavaScript in the browser console

Let me know if you need help with anything!
You: I want to list all the tables.
2025-09-24 17:31:15,839 - INFO - HTTP Request: POST https://api.groq.com/openai/v1/chat/completions "HTTP/1.1 200 OK"
2025-09-24 17:31:15,840 - INFO -
Assistant: ```json
{
  "tool": "list_tables",
  "arguments": {}
}
'```
You:

This is not actually calling the MCP tool list_table, because the triple backticks fences make the response unparsable by json.loads().

Therefore, I add 'without the triple backticks fences' explicitly in the system message. Now the LLM is outputting parsable json, and the tools can be called correctly and smoothly.

python main.py
You: What tools do you have?
2025-09-24 18:05:59,524 - INFO - HTTP Request: POST https://api.groq.com/openai/v1/chat/completions "HTTP/1.1 200 OK"
2025-09-24 18:05:59,525 - INFO - 
Assistant: I have the following tools:

1. `read_query`: Execute a SELECT query on the SQLite database
2. `write_query`: Execute an INSERT, UPDATE, or DELETE query on the SQLite database
3. `create_table`: Create a new table in the SQLite database
4. `list_tables`: List all tables in the SQLite database
5. `describe_table`: Get the schema information for a specific table
6. `append_insight`: Add a business insight to the memo
7. `puppeteer_navigate`: Navigate to a URL
8. `puppeteer_screenshot`: Take a screenshot of the current page or a specific element
9. `puppeteer_click`: Click an element on the page
10. `puppeteer_fill`: Fill out an input field
11. `puppeteer_select`: Select an element on the page with Select tag
12. `puppeteer_hover`: Hover an element on the page
13. `puppeteer_evaluate`: Execute JavaScript in the browser console

Let me know if you'd like to use any of these tools!
You: I want to list all the tables.
2025-09-24 18:06:08,181 - INFO - HTTP Request: POST https://api.groq.com/openai/v1/chat/completions "HTTP/1.1 200 OK"
2025-09-24 18:06:08,181 - INFO - 
Assistant: {
 "tool": "list_tables",
 "arguments": {}
}
2025-09-24 18:06:08,182 - INFO - Executing tool: list_tables
2025-09-24 18:06:08,182 - INFO - With arguments: {}
2025-09-24 18:06:08,184 - INFO - Executing list_tables...
2025-09-24 18:06:09,957 - INFO - HTTP Request: POST https://api.groq.com/openai/v1/chat/completions "HTTP/1.1 200 OK"
2025-09-24 18:06:09,959 - INFO - 
Final response: The database contains the following tables:

* products

Let me know what you'd like to do next!
You: Show me the contents of the products table.
2025-09-24 18:06:25,490 - INFO - HTTP Request: POST https://api.groq.com/openai/v1/chat/completions "HTTP/1.1 200 OK"
2025-09-24 18:06:25,493 - INFO - 
Assistant: {
 "tool": "read_query",
 "arguments": {
 "query": "SELECT * FROM products"
 }
}
2025-09-24 18:06:25,494 - INFO - Executing tool: read_query
2025-09-24 18:06:25,495 - INFO - With arguments: {'query': 'SELECT * FROM products'}
2025-09-24 18:06:25,505 - INFO - Executing read_query...
2025-09-24 18:06:27,951 - INFO - HTTP Request: POST https://api.groq.com/openai/v1/chat/completions "HTTP/1.1 200 OK"
2025-09-24 18:06:27,954 - INFO - 
Final response: The products table contains the following data:

| id | name | price |
| --- | --- | --- |
| 1 | Widget | 19.99 |
| 2 | Gadget | 29.99 |
| 3 | Gizmo | 39.99 |
| 4 | Smart Watch | 199.99 |
| 5 | Wireless Earbuds | 89.99 |
| 6 | Portable Charger | 24.99 |
| 7 | Bluetooth Speaker | 79.99 |
| 8 | Phone Stand | 15.99 |
| 9 | Laptop Sleeve | 34.99 |
| 10 | Mini Drone | 299.99 |
| 11 | LED Desk Lamp | 45.99 |
| 12 | Keyboard | 129.99 |
| 13 | Mouse Pad | 12.99 |
| 14 | USB Hub | 49.99 |
| 15 | Webcam | 69.99 |
| 16 | Screen Protector | 9.99 |
| 17 | Travel Adapter | 27.99 |
| 18 | Gaming Headset | 159.99 |
| 19 | Fitness Tracker | 119.99 |
| 20 | Portable SSD | 179.99 |

Let me know what you'd like to do next!
You:

How Has This Been Tested?

Tested with the default LLM model with default parameters in the example:

url = "https://api.groq.com/openai/v1/chat/completions"
headers = {
    "Content-Type": "application/json",
    "Authorization": f"Bearer {self.api_key}",
}
payload = {
    "messages": messages,
    "model": "meta-llama/llama-4-scout-17b-16e-instruct",
    "temperature": 0.7,
    "max_tokens": 4096,
    "top_p": 1,
    "stream": False,
    "stop": None,
}

Breaking Changes

No breaking changes.

Types of changes

• Bug fix (non-breaking change which fixes an issue)
• New feature (non-breaking change which adds functionality)
• Breaking change (fix or feature that would cause existing functionality to change)
• Documentation update

Checklist

• I have read the MCP Documentation
• My code follows the repository's style guidelines
• New and existing tests pass locally
• I have added appropriate error handling
• I have added or updated documentation as needed

[felixweinberger]

Hi @yukuanj thank you for this contribution!

I tested out and verified that the example you show is indeed broken in the same way for me - however, checking out your branch here doesn't consistently resolve the issue for me. Sometimes it works, sometimes it doesn't.

It still ends up wrapping the tool call in backticks - to be less brittle, I think we'd want to update process_llm_response in this file instead to handle the case when json ... is sent back?

[yukuanj]

@felixweinberger Thank you so much for reviewing and testing out this pull request.

I strongly agree with your point that we should update process_llm_response in this file, instead of solely relying on prompting LLMs.

What I changed

We only attempt a tool call when the response is a single JSON object, optionally wrapped in a fenced code block.
Both of these forms are supported:

1. json {...}
2. {...}
   If there’s any extra text before/after the JSON, we treat it as a normal reply (no tool execution).

How it works

A small regex strips a single fenced block (with or without the word 'json') and then try json.loads().

Example session

python main.py
You: What tools do you have?
2025-09-24 23:23:21,106 - INFO - HTTP Request: POST https://api.groq.com/openai/v1/chat/completions "HTTP/1.1 200 OK"
2025-09-24 23:23:21,107 - INFO - 
Assistant: I have the following tools:

1. `read_query`: Execute a SELECT query on the SQLite database
2. `write_query`: Execute an INSERT, UPDATE, or DELETE query on the SQLite database
4. `create_table`: Create a new table in the SQLite database
5. `list_tables`: List all tables in the SQLite database
6. `describe_table`: Get the schema information for a specific table
7. `append_insight`: Add a business insight to the memo
8. `puppeteer_navigate`: Navigate to a URL
9. `puppeteer_screenshot`: Take a screenshot of the current page or a specific element
10. `puppeteer_click`: Click an element on the page
11. `puppeteer_fill`: Fill out an input field
12. `puppeteer_select`: Select an element on the page with Select tag
13. `puppeteer_hover`: Hover an element on the page
14. `puppeteer_evaluate`: Execute JavaScript in the browser console

Let me know if you need help with anything!
You: I want to list all the tables.
2025-09-24 23:23:25,922 - INFO - HTTP Request: POST https://api.groq.com/openai/v1/chat/completions "HTTP/1.1 200 OK"
2025-09-24 23:23:25,925 - INFO - 
Assistant: ```json
{
  "tool": "list_tables",
  "arguments": {}
}
`` `
2025-09-24 23:23:25,926 - INFO - Executing tool: list_tables
2025-09-24 23:23:25,927 - INFO - With arguments: {}
2025-09-24 23:23:25,934 - INFO - Executing list_tables...
2025-09-24 23:23:27,664 - INFO - HTTP Request: POST https://api.groq.com/openai/v1/chat/completions "HTTP/1.1 200 OK"
2025-09-24 23:23:27,667 - INFO - 
Final response: The database contains the following tables:

- products

Let me know if you need help with anything else!
You:

Looking forward to your feedback!

[yukuanj]

@felixweinberger Hi Felix! I’ve updated the code so that it now passes the checks. Could you please take a look when you get a chance?

[felixweinberger]

Thank you for making the changes, lgtm!