aster-info-mcp

Instructions

Fetch Premium Index 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, markPrice, indexPrice, lastFundingRate, and nextFundingTime.

Raises:
    Exception: If the API request fails or data processing encounters an error.

Implementation Reference

• main.py:248-307 (handler)

  Handler function for the get_premium_index tool. It fetches premium index data from the Aster Finance API endpoint /fapi/v1/premiumIndex, processes the JSON response using pandas to create a formatted Markdown table with columns: symbol, markPrice, indexPrice, lastFundingRate, nextFundingTime. Supports optional symbol parameter or all symbols. Includes error handling for HTTP and processing errors. The @mcp.tool() decorator registers it as an MCP tool.

  @mcp.tool()
  async def get_premium_index(
      symbol: Optional[str] = None
  ) -> str:
      """
      Fetch Premium Index 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, markPrice, indexPrice, lastFundingRate, and nextFundingTime.
      
      Raises:
          Exception: If the API request fails or data processing encounters an error.
      """
      endpoint = "/fapi/v1/premiumIndex"
      
      # 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
              premium_data = response.json()
              
              # Handle single symbol (dict) or all symbols (list of dicts)
              if isinstance(premium_data, dict):
                  premium_data = [premium_data]
              
              # Create pandas DataFrame
              df = pd.DataFrame(premium_data)
              
              # Convert nextFundingTime to readable format
              df["nextFundingTime"] = pd.to_datetime(df["nextFundingTime"], unit="ms")
              
              # Select relevant columns and format numbers
              df = df[["symbol", "markPrice", "indexPrice", "lastFundingRate", "nextFundingTime"]]
              df["markPrice"] = df["markPrice"].astype(float).round(8)
              df["indexPrice"] = df["indexPrice"].astype(float).round(8)
              df["lastFundingRate"] = df["lastFundingRate"].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 Premium Index data: {str(e)}")