Merge pull request #96 from MarcSkovMadsen/enhancement/windows-fixes

windows fixes

Author: MarcSkovMadsen

docs/assets/images/display-tool-feed-dashboard.png

@@ -116,7 +116,7 @@ URLs follow the pattern: `http://host:port/view?id={snippet_id}`
 The server can be configured via environment variables or CLI flags:
 
 - `PORT`: Port number (default: 5005)
-- `ADDRESS`: Host address (default: 127.0.0.1)
+- `ADDRESS`: Host address (default: localhost)
 - `DISPLAY_DB_PATH`: Database file location
 
 ## Design Principles

docs/assets/images/display-tool-feed.png

@@ -33,7 +33,11 @@ The Display Server is included with the `holoviz-mcp` package. Please [make sure
 Now that you have the server installed, let's start it:
 
 ```bash
+# If holoviz-mcp installed as package
 display-server
+
+# If holoviz-mcp installed as uv tool
+uvx --from holoviz-mcp display-server
 ```
 
 You should see output like this:
@@ -42,10 +46,10 @@ You should see output like this:
 Starting Display Server...
 Display Server running at:
 
-  - Add: http://127.0.0.1:5005/add
-  - Feed: http://127.0.0.1:5005/feed
-  - Admin: http://127.0.0.1:5005/admin
-  - API: http://127.0.0.1:5005/api
+  - Add: [http://localhost:5005/add](http://localhost:5005/add)
+  - Feed: [http://localhost:5005/feed](http://localhost:5005/feed)
+  - Admin: [http://localhost:5005/admin](http://localhost:5005/admin)
+  - API: [http://localhost:5005/api](http://localhost:5005/api)
 ```
 
 Great! Your server is now running. Keep this terminal window open while you work through the tutorial.
@@ -65,7 +69,7 @@ Great! Your server is now running. Keep this terminal window open while you work
 
 Let's create your first interactive visualization using the web interface.
 
-Open your web browser and navigate to [`http://127.0.0.1:5005/add`](http://127.0.0.1:5005/add). You'll see a form for creating visualizations.
+Open your web browser and navigate to [`http://localhost:5005/add`](http://localhost:5005/add). You'll see a form for creating visualizations.
 
 Now, let's create a simple bar chart. In the code editor, enter the following Python code:
 
@@ -98,7 +102,7 @@ Click the **Submit** button. You should see a success message with a link to vie
 
 ## Step 4: View Your Visualization
 
-After submitting your code, click the link provided on the Add page. This will take you to a unique URL like `http://127.0.0.1:5005/view?id=abc123` where your visualization is displayed.
+After submitting your code, click the link provided on the Add page. This will take you to a unique URL like `http://localhost:5005/view?id=abc123` where your visualization is displayed.
 
 ![View Page](../assets/images/display-manager-view.png)
 
@@ -111,7 +115,7 @@ You should now see your interactive bar chart! Try hovering over the bars - you'
 
 As you create more visualizations, you'll want an easy way to browse them. Let's check out the Feed page.
 
-Navigate to [`http://127.0.0.1:5005/feed`](http://127.0.0.1:5005/feed). Here you'll see a list view of your recent visualizations, including:
+Navigate to [`http://localhost:5005/feed`](http://localhost:5005/feed). Here you'll see a list view of your recent visualizations, including:
 
 - The visualization name and description
 - When it was created
@@ -125,7 +129,7 @@ The Feed page automatically updates to show your most recent work.
 
 Now let's explore the Admin page where you can manage all your visualizations.
 
-Visit [`http://127.0.0.1:5005/admin`](http://127.0.0.1:5005/admin). This page provides a table view of all your snippets where you can:
+Visit [`http://localhost:5005/admin`](http://localhost:5005/admin). This page provides a table view of all your snippets where you can:
 
 - See detailed information about each snippet
 - Delete visualizations you no longer need
@@ -176,7 +180,7 @@ import requests
 
 # Create a visualization
 response = requests.post(
-    "http://127.0.0.1:5005/api/snippet",
+    "http://localhost:5005/api/snippet",
     headers={"Content-Type": "application/json"},
     json={
         "code": "a='Hello, HoloViz MCP!'\na",
@@ -197,6 +201,11 @@ python script.py
 
 You should see output showing the status code (200 for success) and the response containing the URL of your new visualization. Visit that URL to see your programmatically-created visualization!
 
+```bash
+Status Code: 200
+Response: {'id': '6541b6b3-2b16-4ef5-ac4f-c8fe6d59ff1c', 'created_at': '2026-01-10T10:23:55.270232+00:00', 'url': 'http://localhost:5005/view?id=6541b6b3-2b16-4ef5-ac4f-c8fe6d59ff1c'}
+```
+
 !!! success "Well Done!"
     You can now create visualizations both interactively through the web interface and programmatically through the REST API.
 

docs/assets/images/display-tool-view.png

@@ -24,8 +24,6 @@ Before starting, ensure you have:
 
 In your IDE or development environment make sure to [start the HoloViz MCP server](getting-started.md/#start-the-server).
 
-The open the *Display Server Feed* at http://localhost:5005/feed
-
 !!! note
     If the [Display Server](display-server.md) is already running separately, please stop it using CTRL+C. The MCP server will automatically start the Display Server.
 
@@ -45,13 +43,15 @@ Your AI assistant will use the `holoviz_display` tool and respond with something
 
 ```
 ✓ Visualization created successfully!
-View at: http://127.0.0.1:5005/view?id={snippet_id}
+View at: http://localhost:5005/view?id={snippet_id}
 ```
 
 Click the URL. You should see:
 
 - An interactive bar chart showing the count of each penguin species
 
+![Interactive Bar Chart](../assets/images/display-tool-view.png)
+
 !!! success "Checkpoint"
     If you see the species distribution in your browser, you've successfully created your first visualization! The chart should be interactive - try hovering over the bars.
 
@@ -70,6 +70,8 @@ The AI will create a new visualization. Click the new URL to see:
 - Interactive tooltips when hovering over points
 - The ability to zoom and pan through the data
 
+![Interactive Scatter Plot](../assets/images/display-tool-view2.png)
+
 !!! tip "What you're learning"
     Each visualization gets its own unique URL that you can bookmark or share. The `holoviz_display` tool handles different chart types automatically based on your natural language request.
 
@@ -95,7 +97,7 @@ This demonstrates how `holoviz_display` can handle multi-step analytical workflo
 Now let's see all your visualizations together. In your browser, navigate to:
 
 ```
-http://127.0.0.1:5005/feed
+http://localhost:5005/feed
 ```
 
 You should see:
@@ -104,6 +106,8 @@ You should see:
 - Creation timestamps
 - "Full Screen" and "Copy Code" buttons for each
 
+![Feed](../assets/images/display-tool-feed.png)
+
 The Feed page automatically updates when new visualizations are created!
 
 ### Refine Results
@@ -136,6 +140,8 @@ The visualization will include:
 - Plots that update automatically when you change widget values
 - A complete dashboard layout
 
+![Penguins Dashboard](../assets/images/display-tool-feed-dashboard.png)
+
 !!! success "Achievement unlocked"
     You've created an interactive dashboard! Behind the scenes, the tool uses Panel's execution methods to enable full applications with reactive components.
 

docs/assets/images/display-tool-view2.png

@@ -13,7 +13,7 @@ server:
 display:
   enabled: true
   port: 5005
-  host: "127.0.0.1"
+  host: "localhost"
   max_restarts: 3
   health_check_interval: 60
   auto_install_packages: true

docs/assets/images/display-tool-view3.png

@@ -164,7 +164,7 @@ class DisplayConfig(BaseModel):
         description="URL of remote display server (e.g., 'http://localhost:5005'). Only used in 'remote' mode.",
     )
     port: int = Field(default=5005, description="Port for the display Panel server (subprocess mode only)")
-    host: str = Field(default="127.0.0.1", description="Host address for the display Panel server (subprocess mode only)")
+    host: str = Field(default="localhost", description="Host address for the display Panel server (subprocess mode only)")
     max_restarts: int = Field(default=3, description="Maximum number of restart attempts for Panel server (subprocess mode only)")
     health_check_interval: int = Field(default=60, description="Health check interval in seconds")
     db_path: Path = Field(