parse_excel
Extract data from Excel files to access sheet contents and structured information for analysis or integration.
Instructions
Parses an Excel file and returns its content including all sheets
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| file_path | Yes | Path to the Excel file to parse |
Implementation Reference
- mcp_tool/tools/excel_tool.py:23-91 (handler)The execute method implements the core logic: validates input, processes file path, checks existence and format, reads all sheets with pandas, converts to structured JSON (file info, sheets with rows/cols/data), returns formatted JSON or errors.
async def execute(self, arguments: dict) -> list[types.TextContent | types.ImageContent | types.EmbeddedResource]: """解析Excel文件并返回内容""" if "file_path" not in arguments: return [types.TextContent( type="text", text="Error: Missing required argument '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"Error: File not found at path: {file_path}" )] if not file_path.lower().endswith(('.xlsx', '.xls', '.xlsm')): return [types.TextContent( type="text", text=f"Error: File is not an Excel file: {file_path}" )] try: # 读取Excel文件中的所有sheet excel_file = pd.ExcelFile(file_path) sheet_names = excel_file.sheet_names result = { "file_name": os.path.basename(file_path), "sheet_count": len(sheet_names), "sheets": {} } # 解析每个sheet for sheet_name in sheet_names: df = pd.read_excel(excel_file, sheet_name=sheet_name) # 将DataFrame转换为字典 sheet_data = df.to_dict(orient='records') # 获取列名 columns = df.columns.tolist() # 获取行数和列数 row_count = len(df) column_count = len(columns) result["sheets"][sheet_name] = { "row_count": row_count, "column_count": column_count, "columns": columns, "data": sheet_data } # 将结果转换为JSON字符串，并格式化输出 result_json = json.dumps(result, ensure_ascii=False, indent=2, default=str) return [types.TextContent( type="text", text=result_json )] except Exception as e: return [types.TextContent( type="text", text=f"Error: Failed to parse Excel file: {str(e)}" )] - mcp_tool/tools/excel_tool.py:12-21 (schema)Defines the input schema: object with required 'file_path' string parameter.
input_schema = { "type": "object", "required": ["file_path"], "properties": { "file_path": { "type": "string", "description": "Path to the Excel file to parse", } }, } - mcp_tool/tools/excel_tool.py:7-11 (registration)Registers the tool class ExcelTool inheriting BaseTool with name 'parse_excel' and description via ToolRegistry decorator.
@ToolRegistry.register class ExcelTool(BaseTool): """Excel解析工具，用于解析Excel文件内容""" name = "parse_excel" description = "Parses an Excel file and returns its content including all sheets"