import React from 'react'; const codeString = `import asyncio from openai import AsyncOpenAI from openai.types.chat import ChatCompletionUserMessageParam from mcp import ClientSession from mcp.client.sse import sse_client from litellm.experimental_mcp_client.tools import ( transform_mcp_tool_to_openai_tool, transform_openai_tool_call_request_to_mcp_tool_call_request, ) async def main(): # Initialize clients client = AsyncOpenAI( api_key="sk-1234", base_url="http://localhost:4000" ) # Connect to MCP async with sse_client("http://localhost:4000/mcp/") as (read, write): async with ClientSession(read, write) as session: await session.initialize() mcp_tools = await session.list_tools() print("List of MCP tools for MCP server:", mcp_tools.tools) # Create message messages = [ ChatCompletionUserMessageParam( content="Send an email about LiteLLM supporting MCP", role="user" ) ] # Request with tools response = await client.chat.completions.create( model="gpt-4o", messages=messages, tools=[transform_mcp_tool_to_openai_tool(tool) for tool in mcp_tools.tools], tool_choice="auto" ) # Handle tool call if response.choices[0].message.tool_calls: tool_call = response.choices[0].message.tool_calls[0] if tool_call: # Convert format mcp_call = transform_openai_tool_call_request_to_mcp_tool_call_request( openai_tool=tool_call.model_dump() ) # Execute tool result = await session.call_tool( name=mcp_call.name, arguments=mcp_call.arguments ) print("Result:", result) # Run it asyncio.run(main())`; export const CodeExample: React.FC = () => { return (

Using MCP Tools

Python integration
            {codeString}
          
); };