diff --git a/docs/source/format/CDataInterface/PyCapsuleInterface.rst b/docs/source/format/CDataInterface/PyCapsuleInterface.rst
index 0c1a01d7c67..03095aa2e93 100644
--- a/docs/source/format/CDataInterface/PyCapsuleInterface.rst
+++ b/docs/source/format/CDataInterface/PyCapsuleInterface.rst
@@ -16,6 +16,8 @@
 .. under the License.
 
 
+.. _arrow-pycapsule-interface:
+
 =============================
 The Arrow PyCapsule Interface
 =============================
diff --git a/docs/source/python/extending_types.rst b/docs/source/python/extending_types.rst
index ee92cebcb54..b7261005e66 100644
--- a/docs/source/python/extending_types.rst
+++ b/docs/source/python/extending_types.rst
@@ -21,6 +21,38 @@
 Extending pyarrow
 =================
 
+Controlling conversion to (Py)Arrow with the PyCapsule Interface
+----------------------------------------------------------------
+
+The :ref:`Arrow C data interface <c-data-interface>` allows moving Arrow data between
+different implementations of Arrow. This is a generic, cross-language interface not
+specific to Python, but for Python libraries this interface is extended with a Python
+specific layer: :ref:`arrow-pycapsule-interface`.
+
+This Python interface ensures that different libraries that support the C Data interface
+can export Arrow data structures in a standard way and recognize each other's objects.
+
+If you have a Python library providing data structures that hold Arrow-compatible data
+under the hood, you can implement the following methods on those objects:
+
+- ``__arrow_c_schema__`` for schema or type-like objects.
+- ``__arrow_c_array__`` for arrays and record batches (contiguous tables).
+- ``__arrow_c_stream__`` for chunked tables or streams of data.
+
+Those methods return `PyCapsule <https://docs.python.org/3/c-api/capsule.html>`__
+objects, and more details on the exact semantics can be found in the
+:ref:`specification <arrow-pycapsule-interface>`.
+
+When your data structures have those methods defined, the PyArrow constructors
+(such as :func:`pyarrow.array` or :func:`pyarrow.table`) will recognize those objects as
+supporting this protocol, and convert them to PyArrow data structures zero-copy. And the
+same can be true for any other library supporting this protocol on ingesting data.
+
+Similarly, if your library has functions that accept user-provided data, you can add
+support for this protocol by checking for the presence of those methods, and
+therefore accept any Arrow data (instead of harcoding support for a specific
+Arrow producer such as PyArrow).
+
 .. _arrow_array_protocol:
 
 Controlling conversion to pyarrow.Array with the ``__arrow_array__`` protocol