diff --git a/README.md b/README.md
index 52d95f1c34e..9aada202470 100644
--- a/README.md
+++ b/README.md
@@ -109,7 +109,7 @@ docker compose up
 
 ### pip-installed Deephaven
 
-Users who wish to use Python but not Docker should use [pip-installed Deephaven](https://deephaven.io/core/docs/tutorials/quickstart-pip/).
+Users who wish to use Python but not Docker should use [pip-installed Deephaven](https://deephaven.io/core/docs/tutorials/quickstart-pip/). For users with Windows operating systems, WSL is **not** required to use Deephaven this way.
 
 ```sh
 pip install --upgrade pip setuptools wheel
@@ -150,18 +150,10 @@ docker compose version
 docker run hello-world
 ```
 
-:::note
-
-Internally, the Java build process will use [Gradle Auto Provisioning](https://docs.gradle.org/current/userguide/toolchains.html#sec:provisioning)
+> **_NOTE:_** Internally, the Java build process will use [Gradle Auto Provisioning](https://docs.gradle.org/current/userguide/toolchains.html#sec:provisioning)
 to download and use the appropriate Java version for building and testing.
 
-:::
-
-:::note
-
-On Windows, all commands must be run inside a WSL 2 terminal.
-
-:::
+> **_NOTE:_** On Windows, all commands must be run inside a WSL 2 terminal.
 
 #### Python
 
diff --git a/py/server/README.md b/py/server/README.md
index b2a77ae785f..4afff714724 100644
--- a/py/server/README.md
+++ b/py/server/README.md
@@ -7,13 +7,16 @@ maximum performance. By taking advantage of the unique streaming table capabilit
 facilities (Kafka, Parquet, CSV, SQL, etc.), Python developers can quickly put together a real-time data processing pipeline
 that is high performing and easy to consume.
 
+If you use a Windows operating system, WSL is **not** required to run Deephaven via pip.
 
 ## Install
+
 Because this package depends on the Deephaven server, it comes preinstalled with Deephaven Docker images and is made 
 available at runtime in the Python console in the Deephaven Web UI.
 
 ## Quick start
-``` python
+
+```python
 from deephaven import read_csv
 from deephaven.stream.kafka.consumer import kafka_consumer, TableType
 from deephaven.plot import Figure, PlotStyle
@@ -27,7 +30,9 @@ plot = Figure() \
 ```
 
 ## Related documentation
+
 * https://deephaven.io/
 
 ## API Reference
-[start here] https://deephaven.io/core/pydoc/
+
+[Start here](https://deephaven.io/core/pydoc/)