create_csv
Create CSV files with headers and optional initial data for structured data storage and management.
Instructions
Create a new CSV file with headers and optional initial data.
Args:
filename: Name of the CSV file to create (without .csv extension)
headers: List of column headers
data: Optional list of rows, where each row is a list of values
Returns:
Dictionary with creation results and file informationInput Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| filename | Yes | ||
| headers | Yes | ||
| data | No |
Output Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Implementation Reference
- csv_mcp_server/server.py:44-65 (handler)MCP tool handler function for 'create_csv', registered via @mcp.tool() decorator. Defines input schema via type annotations and delegates execution to CSVManager.create_csv.
@mcp.tool() def create_csv( filename: str, headers: List[str], data: Optional[List[List[Any]]] = None ) -> Dict[str, Any]: """ Create a new CSV file with headers and optional initial data. Args: filename: Name of the CSV file to create (without .csv extension) headers: List of column headers data: Optional list of rows, where each row is a list of values Returns: Dictionary with creation results and file information """ try: return csv_manager.create_csv(filename, headers, data) except Exception as e: return {"success": False, "error": str(e)} - Core helper method in CSVManager class that implements the CSV file creation logic using pandas, including path validation, DataFrame creation, and file writing.
def create_csv(self, filename: str, headers: List[str], data: Optional[List[List[Any]]] = None) -> Dict[str, Any]: """Create a new CSV file with headers and optional initial data.""" filepath = self._get_file_path(filename) if filepath.exists(): raise FileExistsError(f"CSV file '{filename}' already exists") try: # Ensure directory exists for absolute paths self._ensure_directory_exists(filepath) # Create DataFrame df = pd.DataFrame(columns=headers) if data: df = pd.DataFrame(data, columns=headers) # Save to CSV df.to_csv(filepath, index=False) self._validate_file_size(filepath) logger.info(f"Created CSV file: {filepath}") return { "success": True, "filename": filename, "filepath": str(filepath), "rows_created": len(df), "columns": headers } except Exception as e: logger.error(f"Failed to create CSV: {e}") raise