code: def _setup_standard_tools(tools, llm, executor, model_kwargs):
      all_standard_tools = []
      mdb_tool = Tool(
          name="MindsDB",
          func=get_exec_call_tool(llm, executor, model_kwargs),
          description="useful to read from databases or tables connected to the mindsdb machine learning package. the action must be a valid simple SQL query, always ending with a semicolon. For example, you can do `show databases;` to list the available data sources, and `show tables;` to list the available tables within each data source.",  # noqa
      )
  
      mdb_meta_tool = Tool(
          name="MDB-Metadata",
          func=get_exec_metadata_tool(llm, executor, model_kwargs),
          description="useful to get column names from a mindsdb table or metadata from a mindsdb data source. the command should be either 1) a data source name, to list all available tables that it exposes, or 2) a string with the format `data_source_name.table_name` (for example, `files.my_table`), to get the table name, table type, column names, data types per column, and amount of rows of the specified table.",  # noqa
      )
      all_standard_tools.append(mdb_tool)
      all_standard_tools.append(mdb_meta_tool)
      langchain_tools = []
      for tool in tools:
          if tool == "mindsdb_write":
              mdb_write_tool = Tool(
                  name="MDB-Write",
                  func=get_mdb_write_tool(executor),
                  description="useful to write into data sources connected to mindsdb. command must be a valid SQL query with syntax: `INSERT INTO data_source_name.table_name (column_name_1, column_name_2, [...]) VALUES (column_1_value_row_1, column_2_value_row_1, [...]), (column_1_value_row_2, column_2_value_row_2, [...]), [...];`. note the command always ends with a semicolon. order of column names and values for each row must be a perfect match. If write fails, try casting value with a function, passing the value without quotes, or truncating string as needed.`.",  # noqa
              )
              all_standard_tools.append(mdb_write_tool)
          else:
              langchain_tools.append(tool)
  
      all_standard_tools += load_tools(langchain_tools)
      return all_standard_tools
  
file_path: mindsdb/mindsdb/integrations/handlers/langchain_handler/tools.py
imports: import tiktoken
  from typing import Callable
  from mindsdb_sql import parse_sql, Insert
  from langchain.utilities import GoogleSerperAPIWrapper
  from langchain.prompts import PromptTemplate
  from langchain.agents import load_tools, Tool
  from langchain.chains.llm import LLMChain
  from langchain.text_splitter import CharacterTextSplitter
  from langchain.chains.combine_documents.stuff import StuffDocumentsChain
  from langchain.chains import ReduceDocumentsChain, MapReduceDocumentsChain
  from mindsdb.interfaces.skills.skill_tool import make_tools_from_skill
label_desc: Use image node_id 4 for calling a global function with example usage: _setup_standard_tools(tools, llm, executor, model_kwargs) and returns: all_standard_tools