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get_stock_fundamental

Retrieve key financial metrics (PER, PBR, Dividend Yield) for a specific stock on the KOSPI/KOSDAQ market within a defined date range, aiding informed investment decisions.

Instructions

Retrieves fundamental data (PER/PBR/Dividend Yield) for a specific stock.

Args: fromdate (str): Start date for retrieval (YYYYMMDD) todate (str): End date for retrieval (YYYYMMDD) ticker (str): Stock ticker symbol Returns: DataFrame: >> get_stock_fundamental("20210104", "20210108", "005930") BPS PER PBR EPS DIV DPS Date 2021-01-08 37528 28.046875 2.369141 3166 1.589844 1416 2021-01-07 37528 26.187500 2.210938 3166 1.709961 1416 2021-01-06 37528 25.953125 2.189453 3166 1.719727 1416 2021-01-05 37528 26.500000 2.240234 3166 1.690430 1416 2021-01-04 37528 26.218750 2.210938 3166 1.709961 1416

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fromdateYes
tickerYes
todateYes

Implementation Reference

  • The @mcp.tool()-decorated function implementing the get_stock_fundamental tool. It validates inputs, calls pykrx.get_market_fundamental_by_date to fetch PER, PBR, Dividend Yield etc., converts DataFrame to sorted dict.
    @mcp.tool() def get_stock_fundamental(fromdate: Union[str, int], todate: Union[str, int], ticker: Union[str, int]) -> Dict[str, Any]: """Retrieves fundamental data (PER/PBR/Dividend Yield) for a specific stock. Args: fromdate (str): Start date for retrieval (YYYYMMDD) todate (str): End date for retrieval (YYYYMMDD) ticker (str): Stock ticker symbol Returns: DataFrame: >> get_stock_fundamental("20210104", "20210108", "005930") BPS PER PBR EPS DIV DPS Date 2021-01-08 37528 28.046875 2.369141 3166 1.589844 1416 2021-01-07 37528 26.187500 2.210938 3166 1.709961 1416 2021-01-06 37528 25.953125 2.189453 3166 1.719727 1416 2021-01-05 37528 26.500000 2.240234 3166 1.690430 1416 2021-01-04 37528 26.218750 2.210938 3166 1.709961 1416 """ # Validate and convert date format def validate_date(date_str: Union[str, int]) -> str: try: if isinstance(date_str, int): date_str = str(date_str) if '-' in date_str: parsed_date = datetime.strptime(date_str, '%Y-%m-%d') return parsed_date.strftime('%Y%m%d') datetime.strptime(date_str, '%Y%m%d') return date_str except ValueError: raise ValueError(f"Date must be in YYYYMMDD format. Input value: {date_str}") def validate_ticker(ticker_str: Union[str, int]) -> str: if isinstance(ticker_str, int): return str(ticker_str) return ticker_str try: fromdate = validate_date(fromdate) todate = validate_date(todate) ticker = validate_ticker(ticker) logging.debug(f"Retrieving stock fundamental data: {ticker}, {fromdate}-{todate}") # Call get_market_fundamental_by_date df = get_market_fundamental_by_date(fromdate, todate, ticker) # Convert DataFrame to dictionary result = df.to_dict(orient='index') # Convert datetime index to string and sort in reverse sorted_items = sorted( ((k.strftime('%Y-%m-%d'), v) for k, v in result.items()), reverse=True ) result = dict(sorted_items) return result except Exception as e: error_message = f"Data retrieval failed: {str(e)}" logging.error(error_message) return {"error": error_message}

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