random-web3-mcp

Instructions

Generate a random array of specified length

Args:
    salt (str, optional): Random number salt value. Defaults to "".
    array_length (int, optional): Array length. Defaults to 1.
    min_value (int, optional): Minimum value. Defaults to 0.
    max_value (int, optional): Maximum value. Defaults to 1000000.
    allow_duplicates (bool, optional): Allow duplicate values. Defaults to True.

Returns:
    str: JSON string containing the random array

Application Scenarios:
1. Batch random number generation
2. Random sampling
3. Test dataset generation
4. Random task assignment

Implementation Reference

• main.py:67-90 (handler)

  MCP tool handler and registration for 'generate_random_array'. Includes input schema via type annotations and docstring. Delegates execution to the helper function in utils.py.

  @mcp.tool()
  async def generate_random_array(salt: str = "", array_length: int = 1, min_value: int = 0, 
                                max_value: int = 1000000, allow_duplicates: bool = True) -> str:
      """Random Array Generator
      
      Generate a random array of specified length
      
      Args:
          salt (str, optional): Random number salt value. Defaults to "".
          array_length (int, optional): Array length. Defaults to 1.
          min_value (int, optional): Minimum value. Defaults to 0.
          max_value (int, optional): Maximum value. Defaults to 1000000.
          allow_duplicates (bool, optional): Allow duplicate values. Defaults to True.
      
      Returns:
          str: JSON string containing the random array
      
      Application Scenarios:
      1. Batch random number generation
      2. Random sampling
      3. Test dataset generation
      4. Random task assignment
      """
      return await random_array_generator(salt, array_length, min_value, max_value, allow_duplicates)

• utils.py:237-265 (helper)

  Core helper function implementing the random array generation logic using blockchain-derived entropy, seed derivation, and NumPy random functions.

  async def random_array_generator(array_length: int = 1, min_value: int = 0, max_value: int = 1000000, allow_duplicates: bool = True, salt: str="") -> Dict:
      """Random array generator"""
      random_num = await get_random_str()
      if not random_num:
          return {"error": "Failed to get random number"}
          
      request_id = generate_request_id(random_num)
      seed = _derive_seed(request_id, salt)
      np.random.seed(seed)
      
      if allow_duplicates:
          random_array = np.random.randint(min_value, max_value + 1, size=array_length).tolist()
      else:
          # Ensure no duplicates
          if (max_value - min_value + 1) < array_length:
              raise ValueError("Range is too small to generate non-duplicate values")
          
          random_array = np.random.choice(
              range(min_value, max_value + 1), 
              size=array_length, 
              replace=False
          ).tolist()
      
      result = {
          "requestId": request_id,
          "randomArray": random_array
      }
      
      return result