To generate test cases for the "Quadruplet Primes" problem, we need to ensure that we generate valid inputs within the specified range and also handle multiple datasets. Here is a test case generator function for this problem:

```python
import random

def generate_primes_up_to(n):
    """ Helper function to generate all prime numbers up to n using the Sieve of Eratosthenes. """
    sieve = [True] * (n + 1)
    sieve[0] = sieve[1] = False  # 0 and 1 are not primes
    for start in range(2, int(n**0.5) + 1):
        if sieve[start]:
            for multiple in range(start * start, n + 1, start):
                sieve[multiple] = False
    return [num for num, is_prime in enumerate(sieve) if is_prime]

def find_quadruplet_primes(primes):
    """ Helper function to find all quadruplet primes from the list of primes. """
    quadruplet_primes = []
    prime_set = set(primes)
    for prime in primes:
        if prime + 2 in prime_set and prime + 6 in prime_set and prime + 8 in prime_set:
            quadruplet_primes.append(prime + 8)
    return quadruplet_primes

def tcgen():
    # Number of datasets
    num_datasets = random.randint(1, 2000)
    
    # Generate a list of datasets
    datasets = [random.randint(13, 10000000) for _ in range(num_datasets)]
    
    # Append 0 at the end to indicate the end of input
    datasets.append(0)
    
    # Generate all primes up to the maximum value in the datasets
    max_n = max(datasets)
    primes = generate_primes_up_to(max_n)
    
    # Find all quadruplet primes
    quadruplet_primes = find_quadruplet_primes(primes)
    
    # Function to find the largest quadruplet prime less than or equal to n
    def largest_quadruplet_prime(n):
        for qp in reversed(quadruplet_primes):
            if qp <= n:
                return qp
        return None
    
    # Generate outputs for each dataset
    outputs = [largest_quadruplet_prime(n) for n in datasets if n != 0]
    
    return datasets, outputs

# Example of usage:
datasets, outputs = tcgen()
print("Sample Input:")
print("\n".join(map(str, datasets)))
print("Sample Output:")
print("\n".join(map(str, outputs)))
```

### Explanation:

1. **generate_primes_up_to**: This helper function generates all prime numbers up to a given number \( n \) using the Sieve of Eratosthenes.

2. **find_quadruplet_primes**: This helper function finds all quadruplet primes from a list of prime numbers. It returns a list of the largest numbers in each quadruplet.

3. **tcgen**: This function:
    - Randomly decides the number of datasets (between 1 and 2000).
    - Generates random values of \( n \) for each dataset within the given range (13 to 10,000,000).
    - Ensures the end of input with a 0.
    - Uses the helper functions to generate all necessary primes and find the quadruplet primes.
    - For each dataset value, finds the largest quadruplet prime that is less than or equal to \( n \) and prepares the output.

This generator provides both the input datasets and the corresponding outputs. You can use the generated inputs to test your solution and verify its correctness against the outputs.