wehub-resource-sync
83 lines
2.6 KiB
Python
83 lines
2.6 KiB
Python
from mcp.server.fastmcp import FastMCP
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from tools import generate, evaluate, visualize
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# Create FastMCP instance
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mcp = FastMCP("sdv_mcp")
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@mcp.tool()
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def sdv_generate(folder_name: str) -> str:
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"""Generate synthetic data based on real data using SDV Synthesizer.
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This tool reads CSV files from the specified folder, creates a synthetic
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version of that data, and saves it to a 'synthetic_data' folder.
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Args:
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folder_name (str): Path to folder containing CSV data files and metadata.json
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Returns:
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str: Success message with information about generated tables
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"""
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try:
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return generate(folder_name)
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except FileNotFoundError as e:
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return f"Error: {str(e)}"
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except RuntimeError as e:
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return f"Error: {str(e)}"
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@mcp.tool()
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def sdv_evaluate(folder_name: str) -> dict:
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"""Evaluate the quality of synthetic data compared to real data.
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This tool compares the synthetic data in the 'synthetic_data' folder
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with the real data in the specified folder and generates quality metrics.
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Args:
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folder_name (str): Path to folder containing the original CSV data files and metadata.json
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Returns:
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dict: Evaluation results including overall score and detailed properties
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"""
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try:
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result = evaluate(folder_name)
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return result
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except FileNotFoundError as e:
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return {"error": f"File not found: {str(e)}"}
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except RuntimeError as e:
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return {"error": f"Evaluation failed: {str(e)}"}
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@mcp.tool()
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def sdv_visualize(
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folder_name: str,
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table_name: str,
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column_name: str,
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) -> str:
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"""Generate visualization comparing real and synthetic data for a specific column.
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This tool creates a visual comparison between the real data in the specified folder
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and the synthetic data in the 'synthetic_data' folder for a particular table column.
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The visualization is saved as a PNG file in the 'evaluation_plots' folder.
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Args:
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folder_name (str): Path to folder containing the original CSV data files and metadata.json
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table_name (str): Name of the table to visualize (must exist in the metadata)
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column_name (str): Name of the column to visualize within the specified table
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Returns:
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str: Success message with the path to the saved visualization or error message
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"""
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try:
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return visualize(folder_name, table_name, column_name)
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except FileNotFoundError as e:
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return f"Error: {str(e)}"
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except RuntimeError as e:
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return f"Error: {str(e)}"
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# Run the server
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if __name__ == "__main__":
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mcp.run(transport="stdio")
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