generate_basic_random
Generate a random integer within a specified range for applications like lottery systems, game randomness, ID generation, or test data creation. Customize with optional salt, minimum, and maximum values.
Instructions
Basic Random Number Generator
Generate a random integer within the specified range
Args:
salt (str, optional): Random number salt value for increased randomness. Defaults to "".
min_value (int, optional): Minimum value (inclusive). Defaults to 0.
max_value (int, optional): Maximum value (inclusive). Defaults to 1000000.
Returns:
str: JSON string containing the random number result
Application Scenarios:
1. Lottery systems
2. Game random numbers
3. Random ID generation
4. Test data generationInput Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| max_value | No | ||
| min_value | No | ||
| salt | No |
Implementation Reference
- main.py:45-66 (handler)The @mcp.tool()-decorated handler function that defines the tool interface, schema via type hints and docstring, registers the tool, and delegates to the core helper implementation.
@mcp.tool() async def generate_basic_random(salt: str = "", min_value: int = 0, max_value: int = 1000000) -> str: """Basic Random Number Generator Generate a random integer within the specified range Args: salt (str, optional): Random number salt value for increased randomness. Defaults to "". min_value (int, optional): Minimum value (inclusive). Defaults to 0. max_value (int, optional): Maximum value (inclusive). Defaults to 1000000. Returns: str: JSON string containing the random number result Application Scenarios: 1. Lottery systems 2. Game random numbers 3. Random ID generation 4. Test data generation """ return await basic_random_generator(min_value=min_value, max_value=max_value, salt=salt) - utils.py:207-235 (helper)Core helper function containing the exact random number generation logic: fetches blockchain entropy via get_random_str(), derives deterministic seed, seeds numpy RNG, generates value in range, returns structured result.
async def basic_random_generator(min_value: int = 0, max_value: int = 1000000, salt: str="") -> dict: """Basic random number generator""" print(f"\nStarting to generate random number, parameters: salt={salt}, min={min_value}, max={max_value}") try: random_num = await get_random_str() if not random_num: print("Failed to get random number") return {"error": "Failed to get random number"} request_id = generate_request_id(random_num) print(f"Generated request ID: {request_id}") seed = _derive_seed(request_id, salt) print(f"Derived seed: {seed}") np.random.seed(seed) random_value = int(np.random.randint(min_value, max_value + 1)) print(f"Generated random value: {random_value}") result = { "requestId": request_id, "randomValue": random_value } print(f"Final result: {result}") return result except Exception as e: print(f"Failed to generate random number: {str(e)}") return {"error": f"Failed to generate random number: {str(e)}"}