大多数人到底怎么在玩 M C P?深度解剖，

import time
def test_latency :
"""
执行延迟测试并返回结果集合 """
start_time = time.time
for _ in range:
perform_requestelapsed_time =- start_time )* /
return elapsed_time
# 测试套件设置 tests=
# 生成报告 print
从print'来看。^} {'StdDev':^}")
print
for name,func in tests:
latencies=
avg_latency=numpy.mean* /
std_dev=numpy.std* /
print
section>


'步骤 '
'评估需求匹配性'/ span>
/ span />
/ span>

//正确异常处理模式 const errorHandlingMiddleware==>{try{//正常业务逻辑next;}catch{conststructuredError={
type的观点是，'server_error',message:'服务器发生意外错误'。details:{
originalErrorMessage:stringify,recoverySuggestions:
},userVisibleMessage:"抱歉,遇到了技术问题,请稍候再试"
};res.status.json;}}，话说回来，//集成到 MCP 框架中 functionwrapToolWithErrorHandling{returnasyncfunction{try{constresultawaitoriginalTool;老实说，returnresult;}catch{console.error;thrownewStructuredError({
从name来看，'TOOL_EXECUTION_FAILED'。message:`执行${originalTool.name}时发生错误`,cause:{errorCode:,stackTrace:}
});}}}，说起来，module.exports={errorHandlingMiddleware。wrapToolWithErrorHandling};


//规范揭露模板 templateDescriptionTemplate=`
名称的观点是，{tool_name}
说到目的。{one_line_purpose}
{primary_use_case}
{secondary_use_case}
*{param_name}:${param_description}
*{param_name}:${param_description}
onevent_trigger:{trigger_event}
dependent_tools:{dependent_tool_list}
alternative_actions:{fallback_actions}
error_handling:
syntax_errors:{handling_syntax_errors}
runtime_errors:{handling_runtime_errors}
example_input:${sample_input_json}
expected_output:${sample_output_json}
`