I made a similar suggestion in issue46821 (thanks Alex for pointing me to this older issue):

Currently, the implementation of @overload (https://github.com/python/cpython/blob/59585d6b2ea50d7bc3a9b336da5bde61367f527c/Lib/typing.py#L2211) simply returns a dummy function and throws away the decorated function. This makes it virtually impossible for type checkers using the runtime function object to find overloads specified at runtime.

In pyanalyze, I worked around this by providing a custom @overload decorator, working something like this:

_overloads: dict[str, list[Callable]] = {}

def _get_key(func: Callable) -> str:
    return f"{func.__module__}.{func.__qualname__}"

def overload(func):
    key = _get_key(func)
    _overloads.setdefault(key, []).append(func)
    return _overload_dummy

def get_overloads_for(func):
    key = _get_key(func)
    return _overloads.get(key, [])

A full implementation will need more error handling.

I'd like to add something like this to typing.py so that other tools can also use this information.

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With my suggested solution, help() would need to call typing.get_overloads_for() to get any overloads for the function. Unlike Raymond's suggestion, we would not need to change the function creation machinery.