# 安装 Python 依赖
pip install pandas numpy talib longport python-dotenv

# 安装 MCP SDK
pip install mcp

# LongPort API 配置
LONGPORT_APP_KEY=your_app_key
LONGPORT_APP_SECRET=your_app_secret
LONGPORT_ACCESS_TOKEN=your_access_token

# 运行测试脚本
python test_stock_indicators.py

# 启动 MCP 服务器
python stock_indicators_mcp.py

{
  "mcpServers": {
    "stock-indicators": {
      "command": "python",
      "args": ["/path/to/nofx/backend/stock_indicators_mcp.py"],
      "env": {
        "LONGPORT_APP_KEY": "your_app_key",
        "LONGPORT_APP_SECRET": "your_app_secret",
        "LONGPORT_ACCESS_TOKEN": "your_access_token"
      }
    }
  }
}

请使用 get_stock_indicators 工具获取 AAPL.US 的 1小时 技术指标

# 安装 MCP Inspector
npx @modelcontextprotocol/inspector python stock_indicators_mcp.py

{
  "symbol": "AAPL.US",
  "timeframe": "1h",
  "current_price": 252.29,
  "price_change_pct": 2.15,
  "current_ema20": 248.50,
  "current_ema60": 245.10,
  "current_macd_hist": 0.523,
  "current_rsi7": 65.2,
  "current_rsi14": 58.3,
  "current_atr14": 4.85,
  "intraday_series": {
    "mid_prices": [250.1, 251.2, 252.0, ...],
    "ema20_values": [247.5, 248.0, 248.5, ...],
    "macd_hist": [0.45, 0.50, 0.52, ...],
    "rsi7_values": [62.5, 64.0, 65.2, ...],
    ...
  },
  "timestamp": "2025-01-17T10:30:00+08:00"
}

@dataclass
class MarketData:
    symbol: str                    # 股票代码
    timeframe: str                 # 时间周期
    current_price: float           # 当前价格
    price_change_pct: float        # 价格变化百分比
    current_ema20: float           # 当前EMA20
    current_ema60: float           # 当前EMA60
    current_macd_hist: float       # 当前MACD柱
    current_rsi7: float            # 当前RSI(7)
    current_rsi14: float           # 当前RSI(14)
    current_atr14: float           # 当前ATR(14)
    intraday_series: IntradaySeriesData  # 日内序列数据
    timestamp: str                 # 时间戳

@dataclass
class IntradaySeriesData:
    mid_prices: List[float]        # 收盘价序列（最近10个）
    volume_values: List[float]     # 成交量序列
    ema20_values: List[float]      # EMA20序列
    ema60_values: List[float]      # EMA60序列
    macd_dif: List[float]          # MACD DIF序列
    macd_dea: List[float]          # MACD DEA序列
    macd_hist: List[float]         # MACD HIST序列
    rsi7_values: List[float]       # RSI7序列
    rsi14_values: List[float]      # RSI14序列
    atr14_values: List[float]      # ATR14序列
    bb_upper: List[float]          # 布林带上轨
    bb_middle: List[float]         # 布林带中轨
    bb_lower: List[float]          # 布林带下轨

from stock_indicators_mcp import StockDataProvider

provider = StockDataProvider()
data = provider.get_market_data("AAPL.US", "1h", 200)

print(f"当前价格: {data.current_price}")
print(f"EMA20: {data.current_ema20}")
print(f"RSI7: {data.current_rsi7}")

symbols = ["AAPL.US"]
timeframes = ["1Y", "1M", "1w", "1d", "4h", "1h"]  # 从年线到小时线

for symbol in symbols:
    for tf in timeframes:
        data = provider.get_market_data(symbol, tf)
        print(f"{symbol} ({tf}): 价格={data.current_price}, RSI7={data.current_rsi7}")

# 月K线 - 适合长期趋势分析
monthly_data = provider.get_market_data("AAPL.US", "1M", limit=60)  # 最近5年月K
print(f"月线趋势: EMA20={monthly_data.current_ema20:.2f}, RSI={monthly_data.current_rsi7:.2f}")

# 季K线 - 适合宏观分析
quarterly_data = provider.get_market_data("AAPL.US", "1Q", limit=40)  # 最近10年季K
print(f"季度趋势: MACD={quarterly_data.current_macd_hist:.3f}")

# 年K线 - 适合超长期分析
yearly_data = provider.get_market_data("AAPL.US", "1Y", limit=20)  # 最近20年年K
print(f"年度表现: 价格变化={yearly_data.price_change_pct:.2f}%")