get_latest_price
Fetch real-time price data from Aster Finance API for specified trading pairs, returning results in a clear Markdown table format. Ideal for quick market insights.
Instructions
Fetch latest price data from Aster Finance API and return as Markdown table text.
Parameters:
symbol (Optional[str]): Trading pair symbol (e.g., 'BTCUSDT', 'ETHUSDT'). Case-insensitive.
If None, returns data for all symbols.
Returns:
str: Markdown table containing symbol and price.
Raises:
Exception: If the API request fails or data processing encounters an error.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| symbol | No |
Implementation Reference
- main.py:438-491 (handler)The main handler function for the 'get_latest_price' tool. It fetches the latest price from the Aster Finance API (/fapi/v1/ticker/price), handles single or multiple symbols, processes the data using pandas into a Markdown table, and includes error handling. The @mcp.tool() decorator registers it as an MCP tool.async def get_latest_price( symbol: Optional[str] = None ) -> str: """ Fetch latest price data from Aster Finance API and return as Markdown table text. Parameters: symbol (Optional[str]): Trading pair symbol (e.g., 'BTCUSDT', 'ETHUSDT'). Case-insensitive. If None, returns data for all symbols. Returns: str: Markdown table containing symbol and price. Raises: Exception: If the API request fails or data processing encounters an error. """ endpoint = "/fapi/v1/ticker/price" # Construct query parameters params = {} if symbol is not None: params["symbol"] = symbol.upper() # Ensure symbol is uppercase (e.g., BTCUSDT) async with httpx.AsyncClient() as client: try: # Make GET request to the API response = await client.get(f"{BASE_URL}{endpoint}", params=params) response.raise_for_status() # Raise exception for 4xx/5xx errors # Parse JSON response price_data = response.json() # Handle single symbol (dict) or all symbols (list of dicts) if isinstance(price_data, dict): price_data = [price_data] # Create pandas DataFrame df = pd.DataFrame(price_data) # Select relevant columns and format numbers df = df[["symbol", "price"]] df["price"] = df["price"].astype(float).round(8) # Convert DataFrame to Markdown table markdown_table = df.to_markdown(index=False) return markdown_table except httpx.HTTPStatusError as e: # Handle HTTP errors (e.g., 400, 429) raise Exception(f"API request failed: {e.response.status_code} - {e.response.text}") except Exception as e: # Handle other errors (e.g., network issues, pandas errors) raise Exception(f"Error processing latest price data: {str(e)}")
- main.py:438-438 (registration)The @mcp.tool() decorator registers the get_latest_price function as an MCP tool.async def get_latest_price(