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marckwei

MCP Yahoo Finance

by marckwei

get_historical_stock_prices

Retrieve historical stock price data for analysis by specifying a stock symbol, time period, and interval. Use this tool to access past market performance from Yahoo Finance.

Instructions

Get historical stock prices for a given stock symbol.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolYesStock symbol in Yahoo Finance format.
periodNoThe period for historical data. Defaults to "1mo". Valid periods: "1d", "5d", "1mo", "3mo", "6mo", "1y", "2y", "5y", "10y", "ytd", "max"
intervalNoThe interval beween data points. Defaults to "1d". Valid intervals: "1d", "5d", "1wk", "1mo", "3mo"

Implementation Reference

  • The core handler function in the YahooFinance class that retrieves and formats historical stock prices using yfinance's Ticker.history method.
    def get_historical_stock_prices( self, symbol: str, period: Literal[ "1d", "5d", "1mo", "3mo", "6mo", "1y", "2y", "5y", "10y", "ytd", "max" ] = "1mo", interval: Literal["1d", "5d", "1wk", "1mo", "3mo"] = "1d", ) -> str: """Get historical stock prices for a given stock symbol. Args: symbol (str): Stock symbol in Yahoo Finance format. period (str): The period for historical data. Defaults to "1mo". Valid periods: "1d", "5d", "1mo", "3mo", "6mo", "1y", "2y", "5y", "10y", "ytd", "max" interval (str): The interval beween data points. Defaults to "1d". Valid intervals: "1d", "5d", "1wk", "1mo", "3mo" """ stock = Ticker(ticker=symbol, session=self.session) prices = stock.history(period=period, interval=interval) if hasattr(prices.index, "date"): prices.index = prices.index.date.astype(str) # type: ignore return f"{prices['Close'].to_json(orient='index')}"
  • Registers all tools including 'get_historical_stock_prices' by generating Tool objects from the YahooFinance methods using generate_tool.
    @server.list_tools() async def list_tools() -> list[Tool]: return [ generate_tool(yf.cmd_run), generate_tool(yf.get_recommendations), generate_tool(yf.get_news), generate_tool(yf.get_current_stock_price), generate_tool(yf.get_stock_price_by_date), generate_tool(yf.get_stock_price_date_range), generate_tool(yf.get_historical_stock_prices), generate_tool(yf.get_dividends), generate_tool(yf.get_income_statement), generate_tool(yf.get_cashflow), generate_tool(yf.get_earning_dates), ]
  • The dispatch logic in server.call_tool() that matches the tool name and invokes the corresponding handler.
    case "get_historical_stock_prices": price = yf.get_historical_stock_prices(**args) return [TextContent(type="text", text=price)]
  • Utility function that inspects the handler function to generate the MCP Tool schema, including input schema from type annotations and docstring descriptions.
    def generate_tool(func: Any) -> Tool: """Generates a tool schema from a Python function.""" signature = inspect.signature(func) docstring = inspect.getdoc(func) or "" param_descriptions = parse_docstring(docstring) schema = { "name": func.__name__, "description": docstring.split("Args:")[0].strip(), "inputSchema": { "type": "object", "properties": {}, }, } for param_name, param in signature.parameters.items(): param_type = ( "number" if param.annotation is float else "string" if param.annotation is str else "string" ) schema["inputSchema"]["properties"][param_name] = { "type": param_type, "description": param_descriptions.get(param_name, ""), } if "required" not in schema["inputSchema"]: schema["inputSchema"]["required"] = [param_name] else: if "=" not in str(param): schema["inputSchema"]["required"].append(param_name) return Tool(**schema)

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