diff --git a/pyproject.toml b/pyproject.toml
index 0a44a9723..069c8b1ed 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -68,10 +68,14 @@ optional-dependencies.docs = [
   "sunpy[map,net]>=5",
 ]
 optional-dependencies.tests = [
+  "beautifulsoup4>4.8.1",
+  "drms",
+  "lxml>=4.9.3,<5",
   "pytest>=8.3.1",
   "pytest-astropy>=0.11",
   "pytest-cov>=6",
   "pytest-xdist>=3.6.1",
+  "zeep>=4.1.0",
 ]
 urls.Changelog = "https://xrtpy.readthedocs.io/en/stable/changelog/index.html"
 urls.Documentation = "https://xrtpy.readthedocs.io"
diff --git a/xrtpy/visualization_GUI/__init__.py b/xrtpy/visualization_GUI/__init__.py
new file mode 100644
index 000000000..2f610f089
--- /dev/null
+++ b/xrtpy/visualization_GUI/__init__.py
@@ -0,0 +1,3 @@
+from xrtpy.visualization_GUI.fov import metadata_downloader
+
+__all__ = ["metadata_downloader"]
diff --git a/xrtpy/visualization_GUI/fov/__init__.py b/xrtpy/visualization_GUI/fov/__init__.py
new file mode 100644
index 000000000..2f610f089
--- /dev/null
+++ b/xrtpy/visualization_GUI/fov/__init__.py
@@ -0,0 +1,3 @@
+from xrtpy.visualization_GUI.fov import metadata_downloader
+
+__all__ = ["metadata_downloader"]
diff --git a/xrtpy/visualization_GUI/fov/metadata_downloader.py b/xrtpy/visualization_GUI/fov/metadata_downloader.py
new file mode 100644
index 000000000..bdf9d6b73
--- /dev/null
+++ b/xrtpy/visualization_GUI/fov/metadata_downloader.py
@@ -0,0 +1,301 @@
+import urllib.request
+
+import numpy as np
+from astropy.io import fits
+from astropy.time import Time
+from scipy.io import readsav
+
+
+def fetch_metadata(xrt_downloaded_files, fast_bool=True):
+    """
+    Query Hinode/XRT data repositories to retrieve either level 0 (fast) or level 1 (slow) metadata
+
+    Parameters:
+    -----------
+    xrt_downloaded_files : ~sunpy.net.fido_factory.UnifiedResponse
+        fido query result for XRT data
+
+    fast_bool : boolean, optional
+        if True, do a fast retrieval of level 0 metadata
+
+    Returns:
+    --------
+    hdul_lis : ~astropy.io.fits.PrimaryHDU
+        HDU list containing the fits header for all XRT observations in your fido search
+    """
+
+    if fast_bool:
+        print("Fast Metadata (Level 0)")
+        return _download_metadata_fast(xrt_downloaded_files)
+    else:
+        print("Slow Metadata (Level 1)")
+        hdul = _download_metadata_slow(xrt_downloaded_files)
+        # hlis = []
+        # for i in range(len(xrt_downloaded_files[0])):
+        #    hlis.append(hdul[i + 2].header)
+        hlis = [hdul[i + 2].header for i in range(len(xrt_downloaded_files[0]))]
+        return hlis
+
+
+def _download_metadata_slow(xrt_downloaded_files):
+    """
+    Query Hinode/XRT data repositories to retrieve level 1 metadata
+
+    Parameters:
+    -----------
+    xrt_downloaded_files : ~sunpy.net.fido_factory.UnifiedResponse
+        fido query result for XRT data
+
+    Returns:
+    --------
+    hdul_lis : ~astropy.io.fits.PrimaryHDU
+        HDU list containing the fits header for all XRT observations in your fido search
+    """
+
+    url_lis = xrt_downloaded_files[0][:]["fileid"]
+    url_str_lis = list(url_lis)
+    primary_hdu = fits.PrimaryHDU(data=np.ones((3, 3)))
+    c1 = fits.Column(name="URL", array=url_str_lis, format="100A")
+    c2 = fits.Column(
+        name="header_int", array=np.asarray(range(len(url_str_lis))) + 2, format="J"
+    )
+    table_hdu = fits.BinTableHDU.from_columns([c1, c2])
+
+    hdu_lis = fits.HDUList([primary_hdu, table_hdu])
+
+    for i in range(len(url_str_lis)):
+        if i % 10 == 0:
+            print(int(1000.0 * i / len(url_str_lis)) / 10.0, "%")
+
+        fsspec_kwargs = {"block_size": 100_000, "cache_type": "bytes"}
+        with fits.open(
+            url_lis[i], use_fsspec=True, fsspec_kwargs=fsspec_kwargs
+        ) as hdul:
+            # Download a single header
+            t_header = hdul[0].header
+            image_hdu = fits.ImageHDU(
+                data=np.ones((100, 100)), header=t_header, name="header" + str(i)
+            )
+        hdu_lis.append(image_hdu)
+    return hdu_lis
+
+
+def _download_metadata_fast(xrt_downloaded_files):
+    """
+    Query Hinode/XRT data repositories to retrieve level 0 metadata
+
+    Parameters:
+    -----------
+    xrt_downloaded_files : ~sunpy.net.fido_factory.UnifiedResponse
+        fido query result for XRT data
+
+    Returns:
+    --------
+    hdul_lis : ~astropy.io.fits.PrimaryHDU
+        HDU list containing the fits header for all XRT observations in your fido search
+    """
+
+    html_str = _get_html_str()
+    file_lis, cat_fi = _date_to_metafile(xrt_downloaded_files)
+    genyl = _get_urls(file_lis, html_str)
+    print("downloading")
+    data_dict_lis = _get_metafile(genyl)
+    print("done")
+    hdu_lis = _match_vso_to_cat(data_dict_lis, cat_fi, xrt_downloaded_files)
+    return hdu_lis
+
+
+def _get_html_str():
+    """
+    Retrieve list of file names for .geny xrtcat files.
+
+    Parameters:
+    -----------
+
+    Returns:
+    --------
+    html_lis : list
+        list of strings for daily xrtcat .geny files
+    """
+    url_start = "https://sot.lmsal.com/data/sot/metadata/sswdb/hinode/xrt/xrt_genxcat/"
+    with urllib.request.urlopen(url_start) as response:  # noqa : S310
+        html = response.read()
+        html_str = html.decode("utf-8")
+    return html_str
+
+
+def _date_to_metafile(xrt_download_list):
+    """
+    (Part of fast metadata retrieval)
+    Get a partial list of daily xrtcat file names cat contain all observations requested
+
+    Parameters:
+    -----------
+    xrt_downloaded_files : ~sunpy.net.fido_factory.UnifiedResponse
+        fido query result for XRT data
+
+    Returns:
+    --------
+    file_lis : list
+        list containing the unique date string portion for each daily .geny file that contain the requested xrt observatio0ns
+    cat_fi: integer list
+        list containing indexes for each observation pointing at the correct daily .geny file
+    """
+    time_lis = xrt_download_list[0]["Start Time"]
+    year_lis = xrt_download_list[0]["Start Time"].ymdhms.year
+    month_lis = xrt_download_list[0]["Start Time"].ymdhms.month
+    day_lis = xrt_download_list[0]["Start Time"].ymdhms.day
+    cat_fi = []
+    file_lis = []
+    for i in range(len(time_lis)):
+        year_str = str(year_lis[i])
+        month_str = str(month_lis[i])
+        day_str = str(day_lis[i])
+        if len(day_str) < 2:
+            day_str = "0" + day_str
+        if len(month_str) < 2:
+            month_str = "0" + month_str
+        ndatei = year_str + month_str + day_str
+        if ndatei in file_lis:
+            cat_fi.append(file_lis.index(ndatei))
+        else:
+            file_lis.append(ndatei)
+            cat_fi.append(file_lis.index(ndatei))
+
+    return file_lis, cat_fi
+
+
+def _get_urls(file_n_lis, html_str):
+    """
+    (Part of fast metadata retrieval)
+    Retrieve the complete file name for each xrtcat file use the unique daily string for each file to search the complete file list
+
+    Parameters:
+    -----------
+    file_n_lis : string list
+        list with strings containing the date portion of the file name for each xrtcat file
+    html_str :
+        a long string containing the unformatted filenames for all xrtcat files
+
+    Returns:
+    --------
+    geny_lis: string list
+        list containing the complete xrtcat file name for all xrtcat files that contain the requested observations
+    """
+
+    nfile = len(file_n_lis)
+    geny_lis = []
+    for i in range(nfile):
+        find_url = "xrt" + file_n_lis[i]
+        findex = html_str.find(find_url)
+        gen_fn = html_str[findex : findex + 35]
+        findex2 = gen_fn.find("geny")
+        gen_fn = gen_fn[: findex2 + 4]
+        geny_lis.append(gen_fn)
+    return geny_lis
+
+
+def _get_metafile(geny_lis):
+    """
+    (Part of fast metadata retrieval)
+    Retrieve metadata for all observations contained within each .geny files listed in geny_lis
+
+    Parameters:
+    -----------
+    geny_lis : string list
+        list containing the complete xrtcat file name for all xrtcat files that contain the requested observations
+
+    Returns:
+    --------
+    data_dict_lis: dictionary list
+        list containing a dictionary for each .geny file, each dictionary containing metadata for all observations listed in each .geny file
+
+    """
+
+    url_start = "https://sot.lmsal.com/data/sot/metadata/sswdb/hinode/xrt/xrt_genxcat/"
+    ngeny = len(geny_lis)
+    data_dict_lis = []
+    for i in range(ngeny):
+        gen_fn = geny_lis[i]
+        f, h = urllib.request.urlretrieve(url_start + gen_fn)  # noqa : S310
+        data2 = readsav(f)["p0"]
+        data_dict2 = {k: data2[k] for k in data2.dtype.names}
+        data_dict_lis.append(data_dict2)
+    return data_dict_lis
+
+
+def _match_vso_to_cat(data_dict_lis, cat_fi, xrt_download):
+    """
+    (Part of fast metadata retrieval)
+    Match list of requested observations to the metadata retrieved from xrtcat
+
+    Parameters:
+    -----------
+    data_dict_lis : list of dictionaries
+        list containing a dictionary for each .geny file, each dictionary containing metadata for all observations listed in each .geny file
+    cat_fi: integer list
+        list containing indexes for each observation pointing at the correct daily .geny file (or at the correct dictionary in data_dict_lis)
+    xrt_download : ~sunpy.net.fido_factory.UnifiedResponse
+        fido query result for XRT data
+    Returns:
+    --------
+    header_lis: list of dictionaries
+        HDU list containing the fits header for all XRT observations in your fido search
+    """
+    n_dict = len(data_dict_lis)
+    cat_time_lis = []
+    for i in range(n_dict):
+        data_dict = data_dict_lis[i]
+        date_obs_cat = data_dict["DATE_OBS"]
+        cat_str = [cat_bin.decode("ascii") for cat_bin in date_obs_cat]
+        cat_time = Time(np.asarray(cat_str), format="isot", scale="utc")
+        cat_time_lis.append(cat_time)
+
+    min_ti_lis = []
+    delt_lis = []
+    delt_lisp = []
+    delt_lism = []
+    header_lis = []
+    for i in range(len(xrt_download[0]["Start Time"])):
+        cat_time = cat_time_lis[cat_fi[i]]
+        stime = xrt_download[0]["Start Time"][i]
+        dealt = cat_time - stime
+        dealt = dealt.value * 24.0 * 3600.0  # convert from days to seconds
+        min_ti = np.argmin(np.abs(dealt))
+        min_ti_lis.append(min_ti)
+        delt_lis.append(dealt[min_ti])
+        try:
+            delt_lisp.append(dealt[min_ti + 1])
+            delt_lism.append(dealt[min_ti - 1])
+        except IndexError:
+            print()
+        header_lis.append(_meta_to_dict(data_dict_lis[cat_fi[i]], min_ti))
+    return header_lis
+
+
+def _meta_to_dict(data_dict, di):
+    """
+    (Part of fast metadata retrieval)
+    Convert ascii metadata for each obseration to a python dictionary
+
+    Parameters:
+    -----------
+    data_dict : dictionary
+        dictionary containing all of the metadata for all observations in a given .geny file
+    di : integer
+        index that matches the observation entry from fido search to the file entry in data_dict
+
+    Returns:
+    --------
+    hdict : dictionary
+        dictionary of all metadata for a single obseration corresponding to index di
+
+    """
+    dkeys = data_dict.keys()
+    hdict = {}
+    for dki in dkeys:
+        try:
+            hdict[dki] = data_dict[dki][di].decode("ascii")
+        except IndexError:  # noqa : PERF203
+            hdict[dki] = data_dict[dki][di]
+    return hdict
diff --git a/xrtpy/visualization_GUI/fov/tests/__init__.py b/xrtpy/visualization_GUI/fov/tests/__init__.py
new file mode 100644
index 000000000..a9a2c5b3b
--- /dev/null
+++ b/xrtpy/visualization_GUI/fov/tests/__init__.py
@@ -0,0 +1 @@
+__all__ = []
diff --git a/xrtpy/visualization_GUI/fov/tests/test_fov.py b/xrtpy/visualization_GUI/fov/tests/test_fov.py
new file mode 100644
index 000000000..b217b99c1
--- /dev/null
+++ b/xrtpy/visualization_GUI/fov/tests/test_fov.py
@@ -0,0 +1,76 @@
+import sys
+
+import pytest
+from sunpy.net import Fido
+from sunpy.net import attrs as a
+
+from xrtpy.visualization_GUI.fov import metadata_downloader as xfetch
+
+pytestmark = pytest.mark.skipif(sys.version_info >= (3, 13), reason="zeep/lxml is not installable on Python 3.13 due to missing prebuilt wheels"
+)
+
+time_range = a.Time("2011-06-07 06:00:00", "2011-06-07 07:30:54")
+instrument = a.Instrument("xrt")
+
+xrt_downloaded_files = Fido.search(time_range, instrument)
+n_files = len(xrt_downloaded_files[0])
+
+html_str = xfetch._get_html_str()
+
+
+@pytest.mark.xfail(xfail_strict=True)
+def test_download():
+    assert n_files == 0
+
+
+@pytest.mark.xfail(xfail_strict=True)
+def test_html():
+    assert len(html_str) == 0
+
+
+@pytest.mark.parametrize(
+    ("argument", "expected_result"),
+    [
+        (
+            "20061017",
+            "xrt20061017_0000_NE7.geny",
+        ),  # pair the argument with the expected result
+        ("20090405", "xrt20090405_0000_NE394.geny"),
+    ],
+)
+def test_get_urls(argument, expected_result):
+    geny_lis = xfetch._get_urls([argument], html_str)
+    genystr = geny_lis[0]
+    assert genystr == expected_result
+
+
+file_lis, cat_fi = xfetch._date_to_metafile(xrt_downloaded_files)
+
+
+def test_date_to_metafile_a():
+    assert file_lis[0] == "20110607"
+
+
+def test_date_to_metafile_b():
+    assert len(file_lis) == 1
+
+
+def test_date_to_metafile_c():
+    assert len(cat_fi) == n_files
+
+
+@pytest.mark.xfail(xfail_strict=True)
+def test_date_to_metafile_d():
+    assert len(cat_fi) == 0
+
+
+@pytest.mark.parametrize(
+    ("argument", "expected_result"),
+    [
+        (True, n_files),  # pair the argument with the expected result
+        (False, n_files),
+    ],
+)
+def test_fetch_metadata(argument, expected_result):
+    hdul = xfetch.fetch_metadata(xrt_downloaded_files, fast_bool=argument)
+    assert len(hdul) == expected_result