kaggle_mcp_server = McpToolset(
    connection_params=StdioConnectionParams(
        server_params=StdioServerParameters(
            command='npx',
            args=[
                '-y',
                'mcp-remote',
                'https://www.kaggle.com/mcp'
            ],
        ),
        timeout=1000
    )
)

kaggle_agent = LlmAgent(
    name = "kaggle_agent",
    model=LiteLlm(model="groq/openai/gpt-oss-20b"),
    instruction="Use the MCP Tool to search, download and perform multiple actions for daatbases in kaggle",
    tools=[kaggle_mcp_server]
)

kaggle_runner = InMemoryRunner(agent=kaggle_agent)
response= await kaggle_runner.run_debug("I need large dataset for weapon detection in multiple scenerious", verbose = True)

---------------------------------------------------------------------------
ValidationError                           Traceback (most recent call last)
Cell In[7], line 2
      1 kaggle_runner = InMemoryRunner(agent=kaggle_agent)
----> 2 response= await kaggle_runner.run_debug("I need large dataset for weapon detection in multiple scenerious", verbose = True)

File ~/programs/personal-programs/5dgai/.venv/lib/python3.11/site-packages/google/adk/runners.py:1023, in Runner.run_debug(self, user_messages, user_id, session_id, run_config, quiet, verbose)
   1020 if not quiet:
   1021   print(f'\nUser > {message}')
-> 1023 async for event in self.run_async(
   1024     user_id=user_id,
   1025     session_id=session.id,
   1026     new_message=types.UserContent(parts=[types.Part(text=message)]),
   1027     run_config=run_config,
   1028 ):
   1029   if not quiet:
   1030     print_event(event, verbose=verbose)

File ~/programs/personal-programs/5dgai/.venv/lib/python3.11/site-packages/google/adk/runners.py:443, in Runner.run_async(self, user_id, session_id, invocation_id, new_message, state_delta, run_config)
    436       asyncio.create_task(
    437           _run_compaction_for_sliding_window(
    438               self.app, session, self.session_service
    439           )
    440       )
    442 async with Aclosing(_run_with_trace(new_message, invocation_id)) as agen:
--> 443   async for event in agen:
    444     yield event

File ~/programs/personal-programs/5dgai/.venv/lib/python3.11/site-packages/google/adk/runners.py:427, in Runner.run_async.<locals>._run_with_trace(new_message, invocation_id)
    417       yield event
    419 async with Aclosing(
    420     self._exec_with_plugin(
    421         invocation_context=invocation_context,
   (...)    425     )
    426 ) as agen:
--> 427   async for event in agen:
    428     yield event
    429 # Run compaction after all events are yielded from the agent.
    430 # (We don't compact in the middle of an invocation, we only compact at the end of an invocation.)

File ~/programs/personal-programs/5dgai/.venv/lib/python3.11/site-packages/google/adk/runners.py:653, in Runner._exec_with_plugin(self, invocation_context, session, execute_fn, is_live_call)
    650 else:
    651   # Step 2: Otherwise continue with normal execution
    652   async with Aclosing(execute_fn(invocation_context)) as agen:
--> 653     async for event in agen:
    654       if not event.partial:
    655         if self._should_append_event(event, is_live_call):

File ~/programs/personal-programs/5dgai/.venv/lib/python3.11/site-packages/google/adk/runners.py:416, in Runner.run_async.<locals>._run_with_trace.<locals>.execute(ctx)
    414 async def execute(ctx: InvocationContext) -> AsyncGenerator[Event]:
    415   async with Aclosing(ctx.agent.run_async(ctx)) as agen:
--> 416     async for event in agen:
    417       yield event

File ~/programs/personal-programs/5dgai/.venv/lib/python3.11/site-packages/google/adk/agents/base_agent.py:294, in BaseAgent.run_async(self, parent_context)
    291   return
    293 async with Aclosing(self._run_async_impl(ctx)) as agen:
--> 294   async for event in agen:
    295     yield event
    297 if ctx.end_invocation:

File ~/programs/personal-programs/5dgai/.venv/lib/python3.11/site-packages/google/adk/agents/llm_agent.py:435, in LlmAgent._run_async_impl(self, ctx)
    433 should_pause = False
    434 async with Aclosing(self._llm_flow.run_async(ctx)) as agen:
--> 435   async for event in agen:
    436     self.__maybe_save_output_to_state(event)
    437     yield event

File ~/programs/personal-programs/5dgai/.venv/lib/python3.11/site-packages/google/adk/flows/llm_flows/base_llm_flow.py:356, in BaseLlmFlow.run_async(self, invocation_context)
    354 last_event = None
    355 async with Aclosing(self._run_one_step_async(invocation_context)) as agen:
--> 356   async for event in agen:
    357     last_event = event
    358     yield event

File ~/programs/personal-programs/5dgai/.venv/lib/python3.11/site-packages/google/adk/flows/llm_flows/base_llm_flow.py:433, in BaseLlmFlow._run_one_step_async(self, invocation_context)
    422 model_response_event = Event(
    423     id=Event.new_id(),
    424     invocation_id=invocation_context.invocation_id,
    425     author=invocation_context.agent.name,
    426     branch=invocation_context.branch,
    427 )
    428 async with Aclosing(
    429     self._call_llm_async(
    430         invocation_context, llm_request, model_response_event
    431     )
    432 ) as agen:
--> 433   async for llm_response in agen:
    434     # Postprocess after calling the LLM.
    435     async with Aclosing(
    436         self._postprocess_async(
    437             invocation_context,
   (...)    441         )
    442     ) as agen:
    443       async for event in agen:
    444         # Update the mutable event id to avoid conflict

File ~/programs/personal-programs/5dgai/.venv/lib/python3.11/site-packages/google/adk/flows/llm_flows/base_llm_flow.py:804, in BaseLlmFlow._call_llm_async(self, invocation_context, llm_request, model_response_event)
    801           yield llm_response
    803 async with Aclosing(_call_llm_with_tracing()) as agen:
--> 804   async for event in agen:
    805     yield event

File ~/programs/personal-programs/5dgai/.venv/lib/python3.11/site-packages/google/adk/flows/llm_flows/base_llm_flow.py:788, in BaseLlmFlow._call_llm_async.<locals>._call_llm_with_tracing()
    775 responses_generator = llm.generate_content_async(
    776     llm_request,
    777     stream=invocation_context.run_config.streaming_mode
    778     == StreamingMode.SSE,
    779 )
    780 async with Aclosing(
    781     self._run_and_handle_error(
    782         responses_generator,
   (...)    786     )
    787 ) as agen:
--> 788   async for llm_response in agen:
    789     trace_call_llm(
    790         invocation_context,
    791         model_response_event.id,
    792         llm_request,
    793         llm_response,
    794     )
    795     # Runs after_model_callback if it exists.

File ~/programs/personal-programs/5dgai/.venv/lib/python3.11/site-packages/google/adk/flows/llm_flows/base_llm_flow.py:998, in BaseLlmFlow._run_and_handle_error(self, response_generator, invocation_context, llm_request, model_response_event)
    996   yield error_response
    997 else:
--> 998   raise model_error

File ~/programs/personal-programs/5dgai/.venv/lib/python3.11/site-packages/google/adk/flows/llm_flows/base_llm_flow.py:982, in BaseLlmFlow._run_and_handle_error(self, response_generator, invocation_context, llm_request, model_response_event)
    980 try:
    981   async with Aclosing(response_generator) as agen:
--> 982     async for response in agen:
    983       yield response
    984 except Exception as model_error:

File ~/programs/personal-programs/5dgai/.venv/lib/python3.11/site-packages/google/adk/models/lite_llm.py:960, in LiteLlm.generate_content_async(self, llm_request, stream)
    956 _append_fallback_user_content_if_missing(llm_request)
    957 logger.debug(_build_request_log(llm_request))
    959 messages, tools, response_format, generation_params = (
--> 960     _get_completion_inputs(llm_request)
    961 )
    963 if "functions" in self._additional_args:
    964   # LiteLLM does not support both tools and functions together.
    965   tools = None

File ~/programs/personal-programs/5dgai/.venv/lib/python3.11/site-packages/google/adk/models/lite_llm.py:718, in _get_completion_inputs(llm_request)
    712 tools: Optional[List[Dict]] = None
    713 if (
    714     llm_request.config
    715     and llm_request.config.tools
    716     and llm_request.config.tools[0].function_declarations
    717 ):
--> 718   tools = [
    719       _function_declaration_to_tool_param(tool)
    720       for tool in llm_request.config.tools[0].function_declarations
    721   ]
    723 # 3. Handle response format
    724 response_format: Optional[types.SchemaUnion] = None

File ~/programs/personal-programs/5dgai/.venv/lib/python3.11/site-packages/google/adk/models/lite_llm.py:719, in <listcomp>(.0)
    712 tools: Optional[List[Dict]] = None
    713 if (
    714     llm_request.config
    715     and llm_request.config.tools
    716     and llm_request.config.tools[0].function_declarations
    717 ):
    718   tools = [
--> 719       _function_declaration_to_tool_param(tool)
    720       for tool in llm_request.config.tools[0].function_declarations
    721   ]
    723 # 3. Handle response format
    724 response_format: Optional[types.SchemaUnion] = None

File ~/programs/personal-programs/5dgai/.venv/lib/python3.11/site-packages/google/adk/models/lite_llm.py:501, in _function_declaration_to_tool_param(function_declaration)
    496 if (
    497     function_declaration.parameters
    498     and function_declaration.parameters.properties
    499 ):
    500   for key, value in function_declaration.parameters.properties.items():
--> 501     properties[key] = _schema_to_dict(value)
    503 tool_params = {
    504     "type": "function",
    505     "function": {
   (...)    512     },
    513 }
    515 if (
    516     function_declaration.parameters
    517     and function_declaration.parameters.required
    518 ):

File ~/programs/personal-programs/5dgai/.venv/lib/python3.11/site-packages/google/adk/models/lite_llm.py:467, in _schema_to_dict(schema)
    464 for key, value in schema_dict["properties"].items():
    465   # value is a dict → rebuild a Schema object and recurse
    466   if isinstance(value, dict):
--> 467     new_props[key] = _schema_to_dict(types.Schema.model_validate(value))
    468   # value is already a Schema instance
    469   elif isinstance(value, types.Schema):

File ~/programs/personal-programs/5dgai/.venv/lib/python3.11/site-packages/pydantic/main.py:716, in BaseModel.model_validate(cls, obj, strict, extra, from_attributes, context, by_alias, by_name)
    710 if by_alias is False and by_name is not True:
    711     raise PydanticUserError(
    712         'At least one of `by_alias` or `by_name` must be set to True.',
    713         code='validate-by-alias-and-name-false',
    714     )
--> 716 return cls.__pydantic_validator__.validate_python(
    717     obj,
    718     strict=strict,
    719     extra=extra,
    720     from_attributes=from_attributes,
    721     context=context,
    722     by_alias=by_alias,
    723     by_name=by_name,
    724 )

ValidationError: 1 validation error for Schema
enum.9
  Input should be a valid string [type=string_type, input_value=None, input_type=NoneType]
    For further information visit https://errors.pydantic.dev/2.12/v/string_type