diff --git a/failslow/failslow/dataloader/marker_data_reader.py b/failslow/failslow/dataloader/marker_data_reader.py
index 7ab8e31b5ff6bcdd8c4ccc54c8f457cd42a0a9eb..6bbff8c640d6157a0a858769e4d35ac383478385 100644
--- a/failslow/failslow/dataloader/marker_data_reader.py
+++ b/failslow/failslow/dataloader/marker_data_reader.py
@@ -4,7 +4,6 @@ import datetime
 import multiprocessing
 import numpy as np
 import pandas as pd
-import matplotlib.pyplot as plt
 from collections import Counter
 from typing import List, Dict, Tuple
 
@@ -412,32 +411,6 @@ class MarkerDataloader:
 
         return selected_indices, comm_ops
 
-    def get_broadcast_ops(self, broadcast_ops="HcclBroadcast"):
-        ''' Use broadcast time estimate step time '''
-        # for csv_file in self.csv_files:
-        #     csv_path = os.path.join(self._root_path, csv_file)
-        #     data_df = self.read_csv(csv_path)
-        #     data_df['start_stamp'] = data_df['start'].apply(self.convert_timestamp2datetime)
-        #     data_df['end_stamp'] = data_df['end'].apply(self.convert_timestamp2datetime)
-        #     data_df.to_csv(f"new_{csv_file}", index=False)
-
-        csv_path = os.path.join(self._root_path, self.csv_files[0])
-        data_df = self.read_csv(csv_path)
-        data_df['start_stamp'] = data_df[TableItem.ex_start_ts].apply(self.convert_timestamp2datetime)
-        # data_df.to_csv("./broadcast_df.csv", index=False)
-        # n = len(data_df)
-        # quarter = n // 4
-        # data_df = data_df[quarter:]
-        mask = data_df[TableItem.name] == broadcast_ops
-        broadcast_df = data_df[mask]
-        logger.info(f"broadcast df length: {len(broadcast_df)}")
-        broadcast_df['start_stamp'] = broadcast_df[TableItem.ex_start_ts].apply(self.convert_timestamp2datetime)
-        # broadcast_df.to_csv("./broadcast_df.csv", index=False)
-        broadcast_df = self._filter_conti_index(broadcast_df)
-        step_time = np.array(broadcast_df[TableItem.ex_start_ts].diff() / 1e6)[2:]
-        logger.info(f"estimate length: {len(broadcast_df)}")
-
-        self.plot_step_time(step_time)
 
     def convert_timestamp2datetime(self, data):
 
@@ -446,21 +419,6 @@ class MarkerDataloader:
         date_time = dt_object.strftime('%Y-%m-%d %H:%M:%S')
         return date_time
 
-    def plot_step_time(self, data):
-        step_time = extract_step_time_from_log(self._root_path)
-        mean_value = np.mean(data)
-        plt.figure(figsize=(10, 6))
-        plt.plot(step_time[10:110], label='GT', marker='^')
-        plt.plot(data[10:110], label='extimate_time', marker='o')
-        # 绘制均值线
-        # plt.axhline(y=mean_value, color='r', linestyle='--', label='Mean')
-        # 设置图表标题和坐标轴标签
-        plt.title('Estimate step time by dataloader.')
-        plt.xlabel('step index')
-        plt.ylabel('latency(ms)')
-        plt.legend()
-        plt.grid(True)
-        plt.show()
 
     @staticmethod
     def _filter_deviation_data(data):
@@ -503,7 +461,6 @@ if __name__ == "__main__":
 
     convert_jsons2csv(_root_path)
     dataloader = MarkerDataloader(_root_path)
-    # all_comm_groups = dataloader.get_broadcast_ops()
     logger.info(f"{dataloader.csv_files}")
     from restore_comm import RestoreComm
 
diff --git a/failslow/setup.py b/failslow/setup.py
index 618f37722267314a85cae082f63158dad5be2127..a881cd6131eddea02ca55b9f17e5aa47eb29c63f 100644
--- a/failslow/setup.py
+++ b/failslow/setup.py
@@ -43,10 +43,9 @@ setup(
     install_requires=[
         "numpy",
         "pandas",
-        "matplotlib",
         "joblib",
         "scikit_learn",
-        "protobuf==3.20.3"
+        "protobuf"
     ],
     entry_points={
         "console_scripts": [
diff --git a/raw_mcp_py39.zip b/raw_mcp_py39.zip
new file mode 100644
index 0000000000000000000000000000000000000000..effba50c7cae2fd4dca3f8da9b46511e80a0a243
Binary files /dev/null and b/raw_mcp_py39.zip differ
diff --git a/test.sh b/test.sh
new file mode 100644
index 0000000000000000000000000000000000000000..1144ea2aa7319ef1da0c6c8493fa259a4a7cc861
--- /dev/null
+++ b/test.sh
@@ -0,0 +1,109 @@
+#!/bin/bash
+# 颜色定义
+COLOR_INFO='\033[34m'    # 蓝色信息
+COLOR_SUCCESS='\033[32m' # 绿色成功
+COLOR_ERROR='\033[31m'   # 红色错误
+COLOR_WARNING='\033[33m' # 黄色警告
+COLOR_RESET='\033[0m'    # 重置颜色
+
+
+#管理员权限启动
+if [[ $(id -u) -ne 0 ]]; then
+  echo -e "${COLOR_ERROR}[Error] 请以root权限运行该脚本！${COLOR_RESET}"
+  return 1
+fi
+#添加代理
+export http_proxy=http://peulerosci:EulerOS_123@proxy.huawei.com:8080
+export https_proxy=http://peulerosci:EulerOS_123@proxy.huawei.com:8080
+export no_proxy=127.0.0.1
+
+#换源
+echo "更新yum源"
+echo "[SHELL]
+name=SHELL
+baseurl=https://eulermaker.compass-ci.openeuler.openatom.cn/api/ems1/repositories/framework-agent/openEuler%3A24.03-LTS-SP2/x86_64/
+enabled=1
+gpgcheck=0
+sslverify=0
+gpgkey=http://repo.openeuler.org/openEuler-24.03-LTS-SP2/OS//RPM-GPG-KEY-openEuler">>/etc/yum.repos.d/shell.repo
+
+yum clean all
+yum makecache
+
+#启动perf
+git config --global http.sslVerify false
+cd /home
+git clone https://gitee.com/zxstty/perf_mcp
+dnf install -y python3-devel python3-pip perf
+pip install pyyaml psutil mcp==1.6.0 -i https://pypi.tuna.tsinghua.edu.cn/simple --trusted-host pypi.tuna.tsinghua.edu.cn
+cd perf_mcp
+firewall-cmd --permanent --add-port=12141/tcp
+firewall-cmd --reload
+nohup python3 src/server.py >perf_mcp.log 2>&1 &
+
+#安装rpm
+dnf install -y openeuler-intelligence-cli openeuler-intelligence-installer
+
+#修改配置文件
+cd /usr/lib/openeuler-intelligence/scripts/5-resource
+sed -i.bak \
+    -e '/^\[llm\]$/,/^\[.*\]$/ s|^endpoint = .*|endpoint = "https://api.deepseek.com"|' \
+    -e '/^\[llm\]$/,/^\[.*\]$/ s|^key = .*|key = "sk-440510c3614a488283f389834085e173"|' \
+    -e '/^\[llm\]$/,/^\[.*\]$/ s|^model = .*|model = "deepseek-chat"|' \
+    -e '/^\[function_call\]$/,/^\[.*\]$/ s|^backend = .*|backend = "openai"|' \
+    -e '/^\[function_call\]$/,/^\[.*\]$/ s|^endpoint = .*|endpoint = "https://api.deepseek.com"|' \
+    -e '/^\[function_call\]$/,/^\[.*\]$/ s|^model = .*|model = "deepseek-chat"|' \
+    -e '/^\[function_call\]$/,/^\[.*\]$/ s|^api_key = .*|api_key = "sk-440510c3614a488283f389834085e173"|' \
+    config.toml
+
+FRAMEWORK_FILE="framework.service"
+
+if [ ! -f "$FRAMEWORK_FILE" ]; then
+    echo "错误：文件 $FRAMEWORK_FILE 不存在！"
+    exit 1
+fi
+echo '[Unit]
+After=network.target nss-lookup.target
+[Service]
+User=root
+WorkingDirectory=/usr/lib/euler-copilot-framework
+Environment="PYTHONPATH=/usr/lib/euler-copilot-framework"
+Environment="CONFIG=/etc/euler-copilot-framework/config.toml"
+Environment="http_proxy=http://peulerosci:EulerOS_123@proxy.huawei.com:8080"
+Environment="https_proxy=http://peulerosci:EulerOS_123@proxy.huawei.com:8080"
+Environment="no_proxy=127.0.0.1"
+ExecStart=/usr/bin/python3 apps/main.py
+ExecReload=/bin/kill -HUP $MAINPID
+Restart=on-failure
+RestartSec=10
+LimitNOFILE=infinity
+[Install]
+WantedBy=multi-user.target' > "$FRAMEWORK_FILE"
+
+CLIENT_FILE="/usr/lib/python3.11/site-packages/openai/_base_client.py"
+
+if [ ! -f "$CLIENT_FILE" ]; then
+    echo "openai未安装 安装中"
+    dnf install -y python3-openai
+fi
+sed -i.bak -E '/(Sync|Async)HttpxClientWrapper\($/,/timeout=cast\(Timeout, timeout\),/ {
+    /timeout=cast\(Timeout, timeout\),/ a\            verify=False
+}' "$CLIENT_FILE"
+
+#启动
+openeuler-intelligence-installer
+echo "开始初始化智能助手"
+sleep 5
+JSON_FILE="/usr/lib/openeuler-intelligence/scripts/5-resource/mcp_config/perf_mcp/config.json"
+
+if [ ! -f "$JSON_FILE" ]; then
+    echo "错误：文件 $JSON_FILE 不存在！"
+    exit 1
+fi
+
+sed -i.bak 's/"perf 分析工具"/"OS智能助手"/g' "$JSON_FILE"
+
+openeuler-intelligence-installer --a init /usr/lib/openeuler-intelligence/scripts/5-resource/mcp_config/perf_mcp/config.json
+openeuler-intelligence-installer --a create /usr/lib/openeuler-intelligence/scripts/5-resource/mcp_config/perf_mcp/config.json
+
+echo "请在命令行输入 oi 进入 shell端使用界面 "
\ No newline at end of file