MonteWalk

Instructions

Retrieves historical price data (OHLCV) for a given symbol.

Args:
    symbol: The ticker symbol (e.g., 'AAPL', 'BTC-USD').
    interval: Data interval. Valid values: "1m", "2m", "5m", "15m", "30m", "60m", "90m", "1h", "1d", "5d", "1wk", "1mo", "3mo".
    period: Data period to download. Valid values: "1d", "5d", "1mo", "3mo", "6mo", "1y", "2y", "5y", "10y", "ytd", "max".
    visualize: If True, returns a candlestick chart instead of raw data.
    
Returns:
    JSON string of OHLCV data or base64-encoded candlestick chart.

Implementation Reference

• tools/market_data.py:27-86 (handler)

  Core handler implementation of the 'get_price' MCP tool. Fetches historical stock/crypto price data (OHLCV) from yfinance with retry logic, optional candlestick visualization, and JSON output.

  def get_price(
      symbol: str, 
      interval: Literal["1m", "2m", "5m", "15m", "30m", "60m", "90m", "1h", "1d", "5d", "1wk", "1mo", "3mo"] = "1d", 
      period: Literal["1d", "5d", "1mo", "3mo", "6mo", "1y", "2y", "5y", "10y", "ytd", "max"] = "1y",
      visualize: bool = False
  ) -> str:
      """
      Retrieves historical price data (OHLCV) for a given symbol.
      
      Args:
          symbol: The ticker symbol (e.g., 'AAPL', 'BTC-USD').
          interval: Data interval. Valid values: "1m", "2m", "5m", "15m", "30m", "60m", "90m", "1h", "1d", "5d", "1wk", "1mo", "3mo".
          period: Data period to download. Valid values: "1d", "5d", "1mo", "3mo", "6mo", "1y", "2y", "5y", "10y", "ytd", "max".
          visualize: If True, returns a candlestick chart instead of raw data.
          
      Returns:
          JSON string of OHLCV data or base64-encoded candlestick chart.
      """
      try:
          ticker = yf.Ticker(symbol)
          history = ticker.history(period=period, interval=interval)
          
          if history.empty:
              logger.warning(f"No price data found for {symbol} (period={period}, interval={interval})")
              return json.dumps([])
          
          # Reset index to make Date a column
          history.reset_index(inplace=True)
          
          if visualize:
              try:
                  from tools.visualizer import plot_candlestick
                  # Convert to DataFrame format expected by visualizer
                  df = history[['Date', 'Open', 'High', 'Low', 'Close']].copy()
                  if 'Volume' in history.columns:
                      df['Volume'] = history['Volume']
                  
                  chart = plot_candlestick(
                      df,
                      title=f"{symbol} - {period} ({interval} interval)",
                      volume='Volume' in df.columns
                  )
                  return chart
              except Exception as e:
                  logger.error(f"Error generating candlestick chart: {e}")
                  # Fall through to return data
          
          # Convert to JSON-friendly format (list of dicts)
          # Convert timestamps to string
          history['Date'] = history['Date'].astype(str)
          
          data = history.to_dict(orient="records")
          logger.info(f"Fetched {len(data)} price records for {symbol}")
          
          return json.dumps(data, indent=2)
          
      except Exception as e:
          logger.error(f"Error fetching price data for {symbol}: {e}")
          return json.dumps([])

• server.py:370-373 (registration)

  MCP tool registration of 'get_price' as part of the 'Market Data' category. The register_tools helper applies the @mcp.tool() decorator to enable the tool in the FastMCP server.

  register_tools(
      [get_price, get_fundamentals, get_orderbook],
      "Market Data"
  )

• tools/portfolio_optimizer.py:17-38 (helper)

  Internal helper function named get_price used within portfolio_optimizer.py for fetching price data in optimization workflows. Not the registered MCP tool.

  def get_price(ticker: str, period: str, interval: str) -> str:
      """
      Fetches historical price data for a given ticker and returns it as a JSON string.
      This is a placeholder to satisfy the new mean_variance_optimize function's dependency.
      In a real scenario, this might be an API call or a more sophisticated data fetcher.
      """
      try:
          data = yf.download(ticker, period=period, interval=interval, progress=False)
          if data.empty:
              return json.dumps([])
          # Rename columns to match expected structure if necessary, e.g., 'Date' instead of index
          data_reset = data.reset_index()
          data_reset['Date'] = data_reset['Date'].dt.strftime('%Y-%m-%d') # Format date as string
          # Select relevant columns, e.g., 'Date', 'Close'
          # The new code expects 'Date' and 'Close' to be present.
          # If other columns are needed, adjust here.
          history_list = data_reset[['Date', 'Close']].to_dict(orient='records')
          return json.dumps(history_list)
      except Exception as e:
          logger.error(f"Error fetching data for {ticker} with yfinance: {e}")
          return json.dumps([])

• app.py:286-286 (registration)

  Inclusion of get_price in the Gradio UI toolbox under 'Market Data' category for demo interface.

  "Market Data": [get_price, get_fundamentals, get_orderbook],