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Chronulus MCP Server

Official

save_forecast

Save Chronulus forecast data and explanations into separate CSV and TXT files. Use this tool to store rescaled predictions and detailed insights for analysis or reference in specified directories.

Instructions

A tool that saves a Chronulus forecast from NormalizedForecaster to separate CSV and TXT files

When to use this tool:

  • Use this tool when you need to save both the forecast data and its explanation to files

  • The forecast data will be saved as a CSV file for data analysis

  • The forecast explanation will be saved as a TXT file for reference

  • Both files will be saved in the same directory specified by output_path

  • This tool can also be used to directly save rescaled predictions without first calling the rescaling tool

How to use this tool:

  • Provide the prediction_id from a previous forecast

  • Specify the output_path where both files should be saved

  • Provide csv_name for the forecast data file (must end in .csv)

  • Provide txt_name for the explanation file (must end in .txt)

  • Optionally provide y_min and y_max to rescale the predictions (defaults to 0)

  • Set invert_scale to True if the target units run in the opposite direction

  • The tool will provide status updates through the MCP context

Input Schema

NameRequiredDescriptionDefault
csv_nameYesThe path where the CSV file should be saved. Should end in .csv
invert_scaleNoSet this flag to true if the scale of the new units will run in the opposite direction from the inputs.
output_pathYesThe path where the CSV file should be saved. Should end in .csv
prediction_idYesThe prediction_id from a prediction result
txt_nameYesThe name of the TXT file to be saved. Should end in .txt
y_maxNoThe expected largest value for the use case. E.g., for product sales, 0 would be the largest possible value would be given by the user or determined from this history of sales for the product in question or a similar product.
y_minNoThe expected smallest value for the use case. E.g., for product sales, 0 would be the least possible value for sales.

Input Schema (JSON Schema)

{ "properties": { "csv_name": { "description": "The path where the CSV file should be saved. Should end in .csv", "title": "Csv Name", "type": "string" }, "invert_scale": { "default": false, "description": "Set this flag to true if the scale of the new units will run in the opposite direction from the inputs.", "title": "Invert Scale", "type": "boolean" }, "output_path": { "description": "The path where the CSV file should be saved. Should end in .csv", "title": "Output Path", "type": "string" }, "prediction_id": { "description": "The prediction_id from a prediction result", "title": "Prediction Id", "type": "string" }, "txt_name": { "description": "The name of the TXT file to be saved. Should end in .txt", "title": "Txt Name", "type": "string" }, "y_max": { "default": 1, "description": "The expected largest value for the use case. E.g., for product sales, 0 would be the largest possible value would be given by the user or determined from this history of sales for the product in question or a similar product.", "title": "Y Max", "type": "number" }, "y_min": { "default": 0, "description": "The expected smallest value for the use case. E.g., for product sales, 0 would be the least possible value for sales.", "title": "Y Min", "type": "number" } }, "required": [ "prediction_id", "output_path", "csv_name", "txt_name" ], "title": "save_forecastArguments", "type": "object" }

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