load_data
Load data from files in formats like CSV, JSON, or XLSX to enable analysis and visualization within the VisiData environment.
Instructions
Load data from a file using VisiData.
Args: file_path: Path to the data file file_type: Optional file type hint (csv, json, xlsx, etc.)
Returns: String representation of the loaded data structure
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| file_path | Yes | ||
| file_type | No |
Output Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Implementation Reference
- src/visidata_mcp/server.py:73-118 (handler)The load_data tool handler that loads data from files (CSV, JSON, Excel, TSV) using pandas and returns basic dataset information including filename, row count, column count, column names, column types, and file size.
@mcp.tool() def load_data(file_path: str, file_type: Optional[str] = None) -> str: """ Load data from a file using VisiData. Args: file_path: Path to the data file file_type: Optional file type hint (csv, json, xlsx, etc.) Returns: String representation of the loaded data structure """ try: # Use pandas as a reliable fallback for common formats import pandas as pd from pathlib import Path file_extension = Path(file_path).suffix.lower() # Load with pandas first for reliability if file_extension == '.csv': df = pd.read_csv(file_path) elif file_extension == '.json': df = pd.read_json(file_path) elif file_extension in ['.xlsx', '.xls']: df = pd.read_excel(file_path) elif file_extension == '.tsv': df = pd.read_csv(file_path, sep='\t') else: # Try CSV as default df = pd.read_csv(file_path) # Get basic information about the dataset info = { "filename": Path(file_path).name, "rows": len(df), "columns": len(df.columns), "column_names": list(df.columns)[:10], # First 10 columns "column_types": [str(df[col].dtype) for col in df.columns[:10]], "file_size": Path(file_path).stat().st_size if Path(file_path).exists() else 0 } return json.dumps(info, indent=2) except Exception as e: return f"Error loading data: {str(e)}\n{traceback.format_exc()}" - src/visidata_mcp/server.py:73-74 (registration)The @mcp.tool() decorator registers the load_data function as an MCP tool with the server.
@mcp.tool() def load_data(file_path: str, file_type: Optional[str] = None) -> str: