MonteWalk

Instructions

Fetches recent news for a symbol and calculates aggregate sentiment.

Args:
    symbol: Ticker symbol.

Returns:
    Aggregate sentiment analysis of recent news.

Implementation Reference

• tools/news_intelligence.py:191-238 (handler)

  The core handler function for the 'get_symbol_sentiment' tool. It fetches the latest 10 news articles for the given symbol using yfinance, analyzes the sentiment of each title using the 'analyze_sentiment' helper, computes the average polarity score, classifies as BULLISH/BEARISH/NEUTRAL, and returns a formatted string summary.

  def get_symbol_sentiment(symbol: str) -> str:
      """
      Fetches recent news for a symbol and calculates aggregate sentiment.
      
      Args:
          symbol: Ticker symbol.
      
      Returns:
          Aggregate sentiment analysis of recent news.
      """
      try:
          ticker = yf.Ticker(symbol)
          news = ticker.news[:10]  # Last 10 articles
          
          if not news:
              return f"No news found for {symbol}"
          
          sentiments = []
          model_used = "Unknown"
          
          for item in news:
              title = item.get("title", "")
              if title:
                  result = analyze_sentiment(title)
                  if "polarity" in result:
                      sentiments.append(result["polarity"])
                      model_used = result.get("model", "Unknown")
          
          if not sentiments:
              return f"No valid news titles for {symbol}"
          
          avg_polarity = sum(sentiments) / len(sentiments)
          
          if avg_polarity > 0.1:
              classification = "BULLISH"
          elif avg_polarity < -0.1:
              classification = "BEARISH"
          else:
              classification = "NEUTRAL"
          
          return (f"Sentiment Analysis for {symbol} ({len(sentiments)} articles):\n"
                  f"Average Polarity: {avg_polarity:.3f}\n"
                  f"Market Sentiment: {classification}\n"
                  f"Model: {model_used}")
          
      except Exception as e:
          return f"Error analyzing sentiment for {symbol}: {str(e)}"

• server.py:405-408 (registration)

  Registration of the 'get_symbol_sentiment' tool (along with related news tools) using the 'register_tools' helper function, which applies the @mcp.tool() decorator to make it available in the MCP server.

  register_tools(
      [get_news, analyze_sentiment, get_symbol_sentiment],
      "News & Sentiment"
  )

• server.py:19-19 (helper)

  Import statement that brings the 'get_symbol_sentiment' function into the server.py scope for registration.

  from tools.news_intelligence import get_news, analyze_sentiment, get_symbol_sentiment