Financial Datasets MCP Server

Instructions

Args:
    ticker: Ticker symbol of the company (e.g. AAPL, GOOGL)
    start_date: Start date of the price data (e.g. 2020-01-01)
    end_date: End date of the price data (e.g. 2020-12-31)
    interval: Interval of the price data (e.g. minute, hour, day, week, month)
    interval_multiplier: Multiplier of the interval (e.g. 1, 2, 3)

Implementation Reference

• server.py:165-198 (handler)

  Handler function decorated with @mcp.tool() that implements the get_historical_stock_prices tool. It fetches historical stock prices via the Financial Datasets API using the make_request helper, processes the response, and returns JSON-formatted prices.

  @mcp.tool()
  async def get_historical_stock_prices(
      ticker: str,
      start_date: str,
      end_date: str,
      interval: str = "day",
      interval_multiplier: int = 1,
  ) -> str:
      """Gets historical stock prices for a company.
  
      Args:
          ticker: Ticker symbol of the company (e.g. AAPL, GOOGL)
          start_date: Start date of the price data (e.g. 2020-01-01)
          end_date: End date of the price data (e.g. 2020-12-31)
          interval: Interval of the price data (e.g. minute, hour, day, week, month)
          interval_multiplier: Multiplier of the interval (e.g. 1, 2, 3)
      """
      # Fetch data from the API
      url = f"{FINANCIAL_DATASETS_API_BASE}/prices/?ticker={ticker}&interval={interval}&interval_multiplier={interval_multiplier}&start_date={start_date}&end_date={end_date}"
      data = await make_request(url)
  
      # Check if data is found
      if not data:
          return "Unable to fetch prices or no prices found."
  
      # Extract the prices
      prices = data.get("prices", [])
  
      # Check if prices are found
      if not prices:
          return "Unable to fetch prices or no prices found."
  
      # Stringify the prices
      return json.dumps(prices, indent=2)

• server.py:25-41 (helper)

  Helper function used by get_historical_stock_prices to make authenticated HTTP requests to the Financial Datasets API.

  async def make_request(url: str) -> dict[str, any] | None:
      """Make a request to the Financial Datasets API with proper error handling."""
      # Load environment variables from .env file
      load_dotenv()
      
      headers = {}
      if api_key := os.environ.get("FINANCIAL_DATASETS_API_KEY"):
          headers["X-API-KEY"] = api_key
  
      async with httpx.AsyncClient() as client:
          try:
              response = await client.get(url, headers=headers, timeout=30.0)
              response.raise_for_status()
              return response.json()
          except Exception as e:
              return {"Error": str(e)}

• server.py:165-165 (registration)

  MCP tool registration decorator for the get_historical_stock_prices handler.

  @mcp.tool()