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MCP Yahoo Finance

by maxscheijen

get_cashflow

Retrieve cash flow statements for a specific stock symbol on Yahoo Finance. Choose between yearly, quarterly, or trailing frequencies to analyze financial data.

Instructions

Get cashflow for a given stock symbol.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
freqNoAt what frequency to get cashflow statements. Defaults to "yearly". Valid freqencies: "yearly", "quarterly", "trainling"
symbolYesStock symbol in Yahoo Finance format.

Implementation Reference

  • Core handler function for the get_cashflow tool. Fetches cashflow statements using yfinance Ticker.get_cashflow() and formats as pretty JSON string.
    def get_cashflow( self, symbol: str, freq: Literal["yearly", "quarterly", "trainling"] = "yearly" ): """Get cashflow for a given stock symbol. Args: symbol (str): Stock symbol in Yahoo Finance format. freq (str): At what frequency to get cashflow statements. Defaults to "yearly". Valid freqencies: "yearly", "quarterly", "trainling" """ stock = Ticker(ticker=symbol, session=self.session) cashflow = stock.get_cashflow(freq=freq, pretty=True) if isinstance(cashflow, pd.DataFrame): cashflow.columns = [str(col.date()) for col in cashflow.columns] return f"{cashflow.to_json(indent=2)}" return f"{cashflow}"
  • Registers the get_cashflow tool in the MCP server's tool list by generating a Tool object from the handler function.
    generate_tool(yf.get_cashflow),
  • Dispatch handler in the MCP server's call_tool method that invokes the get_cashflow function with arguments and returns the result as TextContent.
    case "get_cashflow": price = yf.get_cashflow(**args) return [TextContent(type="text", text=price)]
  • Helper utility that inspects the handler function to generate the MCP Tool object, including input schema from signature and docstring.
    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)
  • Type annotations and signature that define the input schema for the tool (symbol: str, freq: Literal[...]).
    def get_cashflow( self, symbol: str, freq: Literal["yearly", "quarterly", "trainling"] = "yearly" ):

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