Model Context
Protocol in Python

async def agent_loop(user_prompt: str):
    messages = [{"role": "user", "content": user_prompt}]
    
    # 1. Fetch tool definitions from MCP Server
    mcp_tools = await mcp_session.list_tools()
    openai_tools = [{
        "type": "function",
        "function": {
            "name": t.name,
            "description": t.description,
            "parameters": t.inputSchema
        }
    } for t in mcp_tools]
    
    while True:
        # 2. Query LLM with capabilities exposed
        response = await openai_client.chat.completions.create(
            model="gpt-4o",
            messages=messages,
            tools=openai_tools
        )
        msg = response.choices[0].message
        messages.append(msg)
        
        if not msg.tool_calls:
            return msg.content # Exit when model returns text
            
        # 3. Resolve tool calls recursively against MCP
        for tool_call in msg.tool_calls:
            name = tool_call.function.name
            args = json.loads(tool_call.function.arguments)
            
            mcp_result = await mcp_session.call_tool(name, args)
            
            messages.append({
                "role": "tool",
                "tool_call_id": tool_call.id,
                "content": mcp_result.content[0].text
            })