load_file
Load CSV or XLSX files into DataFrames for data analysis. Specify sheet names for XLSX files and customize DataFrame names as needed.
Instructions
Load Data File Tool
Purpose: Load a local CSV or XLSX file into a DataFrame.
Usage Notes: • If a df_name is not provided, the tool will automatically assign names sequentially as df_1, df_2, and so on. • For XLSX files, you can specify the sheet_name. If not provided, the first sheet will be loaded.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| file_path | Yes | ||
| df_name | No | ||
| sheet_name | No |
Implementation Reference
- src/mcp_data_analyzer/server.py:174-198 (handler)The core handler function in ScriptRunner class that implements the load_file tool logic: loads CSV or XLSX files into a pandas DataFrame, stores it in self.data with a given or auto-generated name, logs notes, and returns success or error TextContent.
def load_file(self, file_path: str, df_name:str = None, sheet_name: Optional[str] = None): self.df_count += 1 if not df_name: df_name = f"df_{self.df_count}" try: file_extension = os.path.splitext(file_path)[1].lower() if file_extension == ".csv": self.data[df_name] = pd.read_csv(file_path) self.notes.append(f"Successfully loaded CSV into dataframe '{df_name}' from '{file_path}'") elif file_extension == ".xlsx": self.data[df_name] = pd.read_excel(file_path, sheet_name=sheet_name) self.notes.append(f"Successfully loaded XLSX into dataframe '{df_name}' from '{file_path}' (sheet: {sheet_name or 'first'})") else: raise ValueError(f"Unsupported file type: {file_extension}. Only .csv and .xlsx are supported.") return [ TextContent(type="text", text=f"Successfully loaded data into dataframe '{df_name}'") ] except Exception as e: error_message = f"Error loading file: {str(e)}" self.notes.append(f"ERROR: {error_message}") return [ TextContent(type="text", text=f"Error: {error_message}") ] - Pydantic schema (BaseModel) defining the input parameters for the load_file tool: file_path (required), optional df_name and sheet_name.
class LoadFile(BaseModel): file_path: str df_name: Optional[str] = None sheet_name: Optional[str] = None - src/mcp_data_analyzer/server.py:299-299 (registration)Registration of the load_file tool in the MCP server's list_tools handler, providing name, description, and input schema.
Tool(name=DataExplorationTools.LOAD_FILE, description=LOAD_FILE_TOOL_DESCRIPTION, inputSchema=LoadFile.model_json_schema()), - src/mcp_data_analyzer/server.py:305-306 (registration)Dispatch logic in the MCP server's call_tool handler that routes calls to the load_file tool to the ScriptRunner instance's load_file method.
if name == DataExplorationTools.LOAD_FILE: return script_runner.load_file(arguments.get("file_path"), arguments.get("df_name"), arguments.get("sheet_name")) - Enum defining the tool names, including LOAD_FILE = 'load_file' used in registration and dispatch.
class DataExplorationTools(str, Enum): LOAD_FILE = "load_file"