diff --git a/pygmt/tests/test_xarray_accessor.py b/pygmt/tests/test_xarray_accessor.py
index 41a8458fac9..99098836be3 100644
--- a/pygmt/tests/test_xarray_accessor.py
+++ b/pygmt/tests/test_xarray_accessor.py
@@ -14,10 +14,19 @@
 from pygmt.datasets import load_earth_relief
 from pygmt.enums import GridRegistration, GridType
 from pygmt.exceptions import GMTValueError
+from pygmt.helpers.testing import load_static_earth_relief
 
 _HAS_NETCDF4 = bool(importlib.util.find_spec("netCDF4"))
 
 
+@pytest.fixture(scope="module", name="grid")
+def fixture_grid():
+    """
+    Load the grid data from the sample earth_relief file.
+    """
+    return load_static_earth_relief()
+
+
 def test_xarray_accessor_gridline_cartesian():
     """
     Check that the accessor returns the correct registration and gtype values for a
@@ -169,3 +178,44 @@ def test_xarray_accessor_tiled_grid_slice_and_add():
     added_grid.gmt.gtype = GridType.GEOGRAPHIC
     assert added_grid.gmt.registration is GridRegistration.PIXEL
     assert added_grid.gmt.gtype is GridType.GEOGRAPHIC
+
+
+def test_xarray_accessor_clip(grid):
+    """
+    Check that the accessor has the clip method and that it works correctly.
+
+    This test is adapted from the `test_grdclip_no_outgrid` test.
+    """
+    clipped_grid = grid.gmt.clip(
+        below=[550, -1000], above=[700, 1000], region=[-53, -49, -19, -16]
+    )
+
+    expected_clipped_grid = xr.DataArray(
+        data=[
+            [1000.0, 570.5, -1000.0, -1000.0],
+            [1000.0, 1000.0, 571.5, 638.5],
+            [555.5, 556.0, 580.0, 1000.0],
+        ],
+        coords={"lon": [-52.5, -51.5, -50.5, -49.5], "lat": [-18.5, -17.5, -16.5]},
+        dims=["lat", "lon"],
+    )
+    xr.testing.assert_allclose(a=clipped_grid, b=expected_clipped_grid)
+
+
+def test_xarray_accessor_histeq(grid):
+    """
+    Check that the accessor has the histeq method and that it works correctly.
+
+    This test is adapted from the `test_equalize_grid_no_outgrid` test.
+    """
+    equalized_grid = grid.gmt.histeq(divisions=2, region=[-52, -48, -22, -18])
+
+    expected_equalized_grid = xr.DataArray(
+        data=[[0, 0, 0, 1], [0, 0, 0, 1], [0, 0, 1, 1], [1, 1, 1, 1]],
+        coords={
+            "lon": [-51.5, -50.5, -49.5, -48.5],
+            "lat": [-21.5, -20.5, -19.5, -18.5],
+        },
+        dims=["lat", "lon"],
+    )
+    xr.testing.assert_allclose(a=equalized_grid, b=expected_equalized_grid)
diff --git a/pygmt/xarray/accessor.py b/pygmt/xarray/accessor.py
index 2899dfe712f..05e162ed78f 100644
--- a/pygmt/xarray/accessor.py
+++ b/pygmt/xarray/accessor.py
@@ -3,12 +3,25 @@
 """
 
 import contextlib
+import functools
 from pathlib import Path
 
 import xarray as xr
 from pygmt.enums import GridRegistration, GridType
 from pygmt.exceptions import GMTValueError
-from pygmt.src.grdinfo import grdinfo
+from pygmt.src import (
+    dimfilter,
+    grdclip,
+    grdcut,
+    grdfill,
+    grdfilter,
+    grdgradient,
+    grdhisteq,
+    grdinfo,
+    grdproject,
+    grdsample,
+    grdtrack,
+)
 
 
 @xr.register_dataarray_accessor("gmt")
@@ -23,6 +36,11 @@ class GMTDataArrayAccessor:
     - ``registration``: Grid registration type :class:`pygmt.enums.GridRegistration`.
     - ``gtype``: Grid coordinate system type :class:`pygmt.enums.GridType`.
 
+    The *gmt* accessor also provides a set of grid-operation methods that enables
+    applying GMT's grid processing functionalities directly to the current
+    :class:`xarray.DataArray` object. See the summary table below for the list of
+    available methods.
+
     Notes
     -----
     When accessed the first time, the *gmt* accessor will first be initialized to the
@@ -150,6 +168,19 @@ class GMTDataArrayAccessor:
     >>> zval.gmt.gtype = GridType.GEOGRAPHIC
     >>> zval.gmt.registration, zval.gmt.gtype
     (<GridRegistration.GRIDLINE: 0>, <GridType.GEOGRAPHIC: 1>)
+
+    Instead of calling a grid-processing function and passing the
+    :class:`xarray.DataArray` object as an input, you can call the corresponding method
+    directly on the object. For example, the following two are equivalent:
+
+    >>> from pygmt.datasets import load_earth_relief
+    >>> grid = load_earth_relief(resolution="30m", region=[10, 30, 15, 25])
+    >>> # Create a new grid from an input grid. Set all values below 1,000 to 0 and all
+    >>> # values above 1,500 to 10,000.
+    >>> # Option 1:
+    >>> new_grid = pygmt.grdclip(grid=grid, below=[1000, 0], above=[1500, 10000])
+    >>> # Option 2:
+    >>> new_grid = grid.gmt.clip(below=[1000, 0], above=[1500, 10000])
     """
 
     def __init__(self, xarray_obj: xr.DataArray):
@@ -200,3 +231,29 @@ def gtype(self, value: GridType | int):
                 value, description="grid coordinate system type", choices=GridType
             )
         self._gtype = GridType(value)
+
+    @staticmethod
+    def _make_method(func):
+        """
+        Create a wrapper method for PyGMT grid-processing methods.
+
+        The :class:`xarray.DataArray` object is passed as the first argument.
+        """
+
+        @functools.wraps(func)
+        def wrapper(self, *args, **kwargs):
+            return func(self._obj, *args, **kwargs)
+
+        return wrapper
+
+    # Accessor methods for grid operations.
+    clip = _make_method(grdclip)
+    cut = _make_method(grdcut)
+    dimfilter = _make_method(dimfilter)
+    histeq = _make_method(grdhisteq.equalize_grid)
+    fill = _make_method(grdfill)
+    filter = _make_method(grdfilter)
+    gradient = _make_method(grdgradient)
+    project = _make_method(grdproject)
+    sample = _make_method(grdsample)
+    track = _make_method(grdtrack)