from dotenv import load_dotenv
from mcp.server.fastmcp import FastMCP
from pydantic import BaseModel
import yfinance as yf
from typing import Dict, List, Optional
class StockAnalysis(BaseModel):
"""
A class that represents the comprehensive stock data for a given stock symbol.
"""
ticker: str
current_price: float
opening_price: float
day_high: float
day_low: float
market_cap: str
pe_ratio: float
dividend_yield: float
fifty_two_week_range: str
recent_news: List[str]
load_dotenv()
mcp = FastMCP("Stock Analysis Server")
@mcp.tool(
name="check_stock_price",
description="Get the current price of a stock symbol",
)
def check_stock_price(stock_symbol: str) -> str:
"""Get the current price of a stock symbol"""
ticker = yf.Ticker(stock_symbol)
hist = ticker.history(period="1d", interval="1d")
current_price = hist['Close'].iloc[-1] if not hist.empty else 0.0
print(f"Current price of {stock_symbol} today: ${current_price}")
return current_price
@mcp.tool(
description="Get comprehensive stock data including price, financial metrics, and recent news.",
)
def get_comprehensive_stock_data(stock_symbol: str) -> StockAnalysis:
"""
Get comprehensive stock data including price, financial metrics, and recent news.
Args:
stock_symbol: The stock ticker symbol (e.g., 'AAPL', 'MSFT')
Returns:
Comprehensive stock analysis including current price, financial metrics, and news
"""
try:
# Initialize ticker object
ticker = yf.Ticker(stock_symbol)
# Get current day's data
hist = ticker.history(period="1d", interval="1d")
# Get company info
info = ticker.info
# Get recent news
news = ticker.news
# Extract key data points
current_price = hist['Close'].iloc[-1] if not hist.empty else 0.0
opening_price = hist['Open'].iloc[0] if not hist.empty else 0.0
day_high = hist['High'].iloc[0] if not hist.empty else 0.0
day_low = hist['Low'].iloc[0] if not hist.empty else 0.0
# Financial metrics
market_cap = info.get('marketCap', 0)
if market_cap:
if market_cap >= 1e12:
market_cap_str = f"{market_cap/1e12:.1f}T"
elif market_cap >= 1e9:
market_cap_str = f"{market_cap/1e9:.1f}B"
elif market_cap >= 1e6:
market_cap_str = f"{market_cap/1e6:.1f}M"
else:
market_cap_str = f"{market_cap:,.0f}"
else:
market_cap_str = "N/A"
pe_ratio = info.get('trailingPE', 0.0)
dividend_yield = info.get('dividendYield', 0.0)
if dividend_yield:
dividend_yield = dividend_yield * 100 # Convert to percentage
# 52-week range
fifty_two_week_low = info.get('fiftyTwoWeekLow', 0)
fifty_two_week_high = info.get('fiftyTwoWeekHigh', 0)
fifty_two_week_range = f"{fifty_two_week_low:.1f} – {fifty_two_week_high:.1f}" if fifty_two_week_low and fifty_two_week_high else "N/A"
# Recent news headlines (limit to 3)
recent_news = []
if news:
for article in news[:3]:
title = article.get('title', '')
if title:
recent_news.append(title)
return StockAnalysis(
ticker=stock_symbol,
current_price=current_price,
opening_price=opening_price,
day_high=day_high,
day_low=day_low,
market_cap=market_cap_str,
pe_ratio=pe_ratio,
dividend_yield=dividend_yield,
fifty_two_week_range=fifty_two_week_range,
recent_news=recent_news,
)
except Exception as e:
# Return error structure
return StockAnalysis(
ticker=stock_symbol,
current_price=0.0,
opening_price=0.0,
day_high=0.0,
day_low=0.0,
market_cap="Error",
pe_ratio=0.0,
dividend_yield=0.0,
fifty_two_week_range="Error",
recent_news=["Unable to fetch news"],
prompt=f"Error retrieving data for {stock_symbol}: {str(e)}"
)
if __name__ == "__main__":
mcp.run(transport="stdio")
