Scientific Computation MCP Server AI Integration

Creates a NumPy array (matrix) with a specified shape and values. Args: shape (list[int]): The shape of the resulting array as a tuple(e.g., (2, 3)). values (list[float]): A flat list of values to populate the array. name (str): The name of the tensor to be stored. Returns: np.ndarray: A NumPy array with the specified shape. Raises: ValueError: If the number of values does not match the product of the shape.

Returns an immutable view of a previously stored NumPy tensor from the in-memory tensor store. Args: name (str): The name of the tensor as stored in the in-store dictionary Returns: dict: The in-store dictionary for tensors

Deletes a tensor from the in-memory tensor store. Args: name (str): The name of the tensor to delete. Raises: ValueError: If the tensor name is not found in the store or if an error occurs during deletion.

Adds two stored tensors element-wise. Args: name_a (str): The name of the first tensor. name_b (str): The name of the second tensor. Returns: np.ndarray: The result of element-wise addition. Raises: ValueError: If the tensor names are not found or shapes are incompatible.

Adds two stored tensors element-wise. Args: name_a (str): The name of the first tensor. name_b (str): The name of the second tensor. Returns: np.ndarray: The result of element-wise subtraction. Raises: ValueError: If the tensor names are not found or shapes are incompatible.