get_us_stock_analysis
Analyze US stock data with technical indicators by providing a ticker symbol and optional analysis period. Evaluate trends and momentum using parameters for symbol and days.
Instructions
미국 주식 종목을 분석합니다.
Args: symbol: 티커 심볼 (예: 'AAPL', 'TSLA', 'NVDA', 'GOOGL') days: 조회 기간 (일수, 기본 120일)
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| symbol | Yes | ||
| days | No |
Output Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Implementation Reference
- server.py:135-220 (handler)The MCP tool handler for 'get_us_stock_analysis' - fetches US stock data via yfinance, computes technical indicators (SMA, RSI, MACD, Bollinger Bands, Ichimoku), and returns analysis as JSON.
def get_us_stock_analysis(symbol: str, days: int = 120) -> str: """미국 주식 종목을 분석합니다. Args: symbol: 티커 심볼 (예: 'AAPL', 'TSLA', 'NVDA', 'GOOGL') days: 조회 기간 (일수, 기본 120일) """ tk = yf.Ticker(symbol) df = tk.history(period=f"{days}d") if df.empty: return f"'{symbol}'에 대한 데이터를 찾을 수 없습니다." if len(df) < 2: return f"'{symbol}'의 데이터가 부족합니다 (거래일 {len(df)}일). 분석 기간을 늘려주세요." info = tk.info name = info.get("shortName", symbol) # 기술적 지표 계산 df['SMA5'] = df['Close'].rolling(5).mean() df['SMA20'] = df['Close'].rolling(20).mean() df['SMA60'] = df['Close'].rolling(60).mean() df['RSI'] = ta.momentum.RSIIndicator(df['Close'], window=14).rsi() macd_ind = ta.trend.MACD(df['Close']) df['MACD'] = macd_ind.macd() df['MACD_signal'] = macd_ind.macd_signal() df['MACD_hist'] = macd_ind.macd_diff() bb = ta.volatility.BollingerBands(df['Close']) df['BB_upper'] = bb.bollinger_hband() df['BB_lower'] = bb.bollinger_lband() ichimoku = ta.trend.IchimokuIndicator(df['High'], df['Low'], window1=9, window2=26, window3=52) df['Ichimoku_conversion'] = ichimoku.ichimoku_conversion_line() df['Ichimoku_base'] = ichimoku.ichimoku_base_line() df['Ichimoku_span_a'] = ichimoku.ichimoku_a() df['Ichimoku_span_b'] = ichimoku.ichimoku_b() df['Ichimoku_lagging'] = df['Close'].shift(-26) latest = df.iloc[-1] prev = df.iloc[-2] result = { "종목명": name, "심볼": symbol, "현재가": round(latest['Close'], 2), "전일대비": round(latest['Close'] - prev['Close'], 2), "등락률": round((latest['Close'] - prev['Close']) / prev['Close'] * 100, 2), "거래량": int(latest['Volume']), "기술적지표": { "SMA5": round(latest['SMA5'], 2) if pd.notna(latest['SMA5']) else None, "SMA20": round(latest['SMA20'], 2) if pd.notna(latest['SMA20']) else None, "SMA60": round(latest['SMA60'], 2) if pd.notna(latest['SMA60']) else None, "RSI_14": round(latest['RSI'], 2) if pd.notna(latest['RSI']) else None, "MACD": round(latest['MACD'], 2) if pd.notna(latest['MACD']) else None, "MACD_signal": round(latest['MACD_signal'], 2) if pd.notna(latest['MACD_signal']) else None, "MACD_histogram": round(latest['MACD_hist'], 2) if pd.notna(latest['MACD_hist']) else None, "볼린저_상단": round(latest['BB_upper'], 2) if pd.notna(latest['BB_upper']) else None, "볼린저_하단": round(latest['BB_lower'], 2) if pd.notna(latest['BB_lower']) else None, "일목_전환선": round(latest['Ichimoku_conversion'], 2) if pd.notna(latest['Ichimoku_conversion']) else None, "일목_기준선": round(latest['Ichimoku_base'], 2) if pd.notna(latest['Ichimoku_base']) else None, "일목_선행스팬A": round(latest['Ichimoku_span_a'], 2) if pd.notna(latest['Ichimoku_span_a']) else None, "일목_선행스팬B": round(latest['Ichimoku_span_b'], 2) if pd.notna(latest['Ichimoku_span_b']) else None, "일목_후행스팬": round(latest['Ichimoku_lagging'], 2) if pd.notna(latest['Ichimoku_lagging']) else None, }, "기간내_최고가": round(df['High'].max(), 2), "기간내_최저가": round(df['Low'].min(), 2), "시가총액": info.get("marketCap"), "52주_최고": info.get("fiftyTwoWeekHigh"), "52주_최저": info.get("fiftyTwoWeekLow"), "PER": info.get("trailingPE"), "최근10일_OHLCV": [] } for _, row in df.tail(10).iterrows(): result["최근10일_OHLCV"].append({ "날짜": str(row.name.date()), "시가": round(row['Open'], 2), "고가": round(row['High'], 2), "저가": round(row['Low'], 2), "종가": round(row['Close'], 2), "거래량": int(row['Volume']) }) return json.dumps(result, ensure_ascii=False, indent=2) - server.py:134-135 (registration)Tool registration via @mcp.tool() decorator on FastMCP instance 'Stock Analyzer' (defined on line 14).
@mcp.tool() def get_us_stock_analysis(symbol: str, days: int = 120) -> str: