MCP Development Framework

Instructions

Implementation Reference

• mcp_tool/tools/csv_tool.py:35-110 (handler)

  The main handler function that executes the parse_csv tool. It reads the CSV file using pandas, detects encoding if needed, provides file info, data preview, and descriptive statistics.

  async def execute(self, arguments: Dict[str, Any]) -> List[types.TextContent]:
      """
      解析CSV文件内容
      
      Args:
          arguments: 参数字典，必须包含'file_path'键，可选'encoding'键
      
      Returns:
          解析结果列表
      """
      if "file_path" not in arguments:
          return [types.TextContent(
              type="text",
              text="错误: 缺少必要参数 'file_path'"
          )]
      
      file_path = arguments["file_path"]
      # 处理文件路径，支持挂载目录的转换
      file_path = self.process_file_path(file_path)
      
      if not os.path.exists(file_path):
          return [types.TextContent(
              type="text",
              text=f"错误: 文件不存在: {file_path}"
          )]
      
      try:
          # 尝试自动检测编码
          encoding = arguments.get("encoding", None)
          if encoding is None:
              try:
                  import chardet
                  with open(file_path, 'rb') as f:
                      raw_data = f.read()
                      encoding = chardet.detect(raw_data)['encoding']
              except ImportError:
                  encoding = 'utf-8'  # 如果没有chardet，默认使用utf-8
          
          # 读取CSV文件
          df = pd.read_csv(file_path, encoding=encoding)
          
          # 获取基本信息
          info = {
              "文件名": os.path.basename(file_path),
              "行数": len(df),
              "列数": len(df.columns),
              "列名": list(df.columns),
              "数据预览": df.head().to_string()
          }
          
          # 生成描述性统计
          stats = df.describe().to_string()
          
          # 组合结果
          result = (
              f"CSV文件解析结果:\n\n"
              f"基本信息:\n"
              f"- 文件名: {info['文件名']}\n"
              f"- 行数: {info['行数']}\n"
              f"- 列数: {info['列数']}\n"
              f"- 列名: {', '.join(info['列名'])}\n\n"
              f"数据预览:\n{info['数据预览']}\n\n"
              f"描述性统计:\n{stats}"
          )
          
          return [types.TextContent(
              type="text",
              text=result
          )]
          
      except Exception as e:
          error_details = traceback.format_exc()
          return [types.TextContent(
              type="text",
              text=f"错误: 处理CSV文件时发生错误: {str(e)}\n{error_details}"
          )] 

• mcp_tool/tools/csv_tool.py:20-33 (schema)

  Input schema defining the parameters for the parse_csv tool: required file_path and optional encoding.

  input_schema = {
      "type": "object",
      "required": ["file_path"],
      "properties": {
          "file_path": {
              "type": "string",
              "description": "CSV文件的本地路径，例如'/path/to/data.csv'",
          },
          "encoding": {
              "type": "string",
              "description": "文件编码格式，例如'utf-8'、'gbk'等，默认自动检测",
          }
      },
  }

• mcp_tool/tools/csv_tool.py:12-19 (registration)

  Tool registration via @ToolRegistry.register decorator, class name CsvTool, and tool name 'parse_csv' assignment.

  @ToolRegistry.register
  class CsvTool(BaseTool):
      """
      CSV文件处理工具，用于解析CSV文件内容
      """
      
      name = "parse_csv"
      description = "解析CSV文件内容，支持各种编码格式"