diff --git a/docs/api.rst b/docs/api.rst
index df323f2f8..618a52919 100644
--- a/docs/api.rst
+++ b/docs/api.rst
@@ -241,6 +241,7 @@ Grid
    Grid.to_geodataframe
    Grid.to_polycollection
    Grid.to_linecollection
+   Grid.plot_edges
    Grid.to_xarray
 
 UxDataArray
diff --git a/docs/user-guide/mpl.ipynb b/docs/user-guide/mpl.ipynb
index c61d436a3..520f1d38e 100644
--- a/docs/user-guide/mpl.ipynb
+++ b/docs/user-guide/mpl.ipynb
@@ -477,6 +477,38 @@
     "ax.set_title(\"LineCollection\")\n",
     "plt.show()"
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1f1e0022-ad9e-44f3-b267-b43030d69e88",
+   "metadata": {},
+   "source": [
+    "To plot only the visible edges of a grid within a local extent, use the {meth}`~uxarray.Grid.plot_edges` method.\n",
+    "This routine automatically extracts the current axis limits and draws only the edges that fall inside those limits.\n",
+    "By avoiding the rendering of off‑screen edges, it can dramatically reduce the amount of work required for high‑resolution grids, leading to faster plot generation and lower memory consumption."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e544b3ab-a045-440b-b9bf-b7f11b5d65bf",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "center = -50, 0\n",
+    "fig, ax = plt.subplots(\n",
+    "    1,\n",
+    "    1,\n",
+    "    constrained_layout=True,\n",
+    "    subplot_kw={\"projection\": ccrs.Orthographic(*center)},\n",
+    ")\n",
+    "ax.add_feature(cfeature.LAND)\n",
+    "ax.add_feature(cfeature.COASTLINE)\n",
+    "ax.set_extent([center[0] + 20, center[0] - 20, center[1] - 10, center[1] + 10])\n",
+    "\n",
+    "uxds.uxgrid.plot_edges(ax=ax, color=\"blue\")\n",
+    "plt.show()"
+   ]
   }
  ],
  "metadata": {
diff --git a/test/test_plot.py b/test/test_plot.py
index 8af794c90..4f9312df1 100644
--- a/test/test_plot.py
+++ b/test/test_plot.py
@@ -4,6 +4,7 @@
 import pytest
 import numpy as np
 
+import matplotlib
 import matplotlib.pyplot as plt
 import cartopy.crs as ccrs
 
@@ -217,3 +218,13 @@ def test_collections_projection_kwarg(gridpath):
     with pytest.warns(FutureWarning):
         pc = uxgrid.to_polycollection(projection=ccrs.PlateCarree())
         lc = uxgrid.to_linecollection(projection=ccrs.PlateCarree())
+
+
+def test_plot_edges(gridpath):
+    uxgrid = ux.open_grid(gridpath("ugrid", "outCSne30", "outCSne30.ug"))
+    fig, ax = plt.subplots(subplot_kw={'projection': ccrs.PlateCarree()})
+    lines = uxgrid.plot_edges(ax=ax, color="green")
+    # check if all edges are plotted
+    assert len(lines) == uxgrid.n_edge
+    # check if the type is correct
+    assert all(isinstance(line, matplotlib.lines.Line2D) for line in lines)
diff --git a/uxarray/grid/grid.py b/uxarray/grid/grid.py
index b940912bb..4265b9fd6 100644
--- a/uxarray/grid/grid.py
+++ b/uxarray/grid/grid.py
@@ -2378,6 +2378,55 @@ def to_linecollection(
 
         return copy.deepcopy(line_collection)
 
+    def plot_edges(
+        self,
+        ax: Optional["cartopy.mpl.geoaxes.GeoAxes"] | None,  # noqa: F821
+        **plot_kwargs,
+    ):
+        """
+        Plot the edges of the grid on a Cartopy map.
+
+        Parameters
+        ----------
+        ax : cartopy.mpl.geoaxes.GeoAxes or None
+            The axes on which to plot. If None, a new global map with PlatteCarree projection is used.
+        **plot_kwargs : dict
+            Additional keyword arguments passed to ``ax.plot`` (e.g., line style,
+            color, linewidth).
+
+        Returns
+        -------
+        list of matplotlib.lines.Line2D
+        """
+
+        import cartopy.crs as ccrs
+        import matplotlib.pyplot as plt
+
+        if ax is None:
+            ax = plt.axes(projection=ccrs.PlateCarree())
+
+        vx, vy, vz = ax.projection.transform_points(
+            ccrs.PlateCarree(), self.node_lon, self.node_lat
+        ).T
+
+        extent = ax.get_extent()
+        vmask = (
+            (vx >= extent[0])
+            * (vx <= extent[1])
+            * (vy >= extent[2])
+            * (vy <= extent[3])
+        )
+        emask = np.any(vmask[self.edge_node_connectivity], axis=-1)
+        edge_node_local = self.edge_node_connectivity.values[emask, :].T
+
+        return ax.plot(
+            self.node_lon.values[edge_node_local],
+            self.node_lat.values[edge_node_local],
+            transform=ccrs.Geodetic(),
+            label=self.source_grid_spec,
+            **plot_kwargs,
+        )
+
     def get_dual(self, check_duplicate_nodes: bool = False):
         """Compute the dual for a grid, which constructs a new grid centered
         around the nodes, where the nodes of the primal become the face centers