Add MCP server support and documentation

README.md

@@ -1,10 +1,10 @@
 ---
 title: GeoSpatial-LiDAR-3D Point Cloud Visualizer
-emoji: 🌎
+emoji: "\U0001F30E"
 colorFrom: blue
 colorTo: purple
 sdk: gradio
-sdk_version: 6.2.0
+sdk_version: "4.43.0"
 app_file: app.py
 pinned: false
 ---
@@ -14,7 +14,7 @@ pinned: false
 A web application for visualizing and analyzing LiDAR point cloud data in 3D.
 
 ![Python](https://img.shields.io/badge/Python-3.9+-blue)
-![Gradio](https://img.shields.io/badge/Gradio-4.0.0+-green)
+![Gradio](https://img.shields.io/badge/Gradio-4.43.0+-green)
 ![License](https://img.shields.io/badge/License-MIT-yellow)
 
 ## Features
@@ -28,6 +28,7 @@ A web application for visualizing and analyzing LiDAR point cloud data in 3D.
 - **Detailed Statistics**: View point counts, coordinate ranges, RGB presence, and segmentation information
 - **Example Files**: Explore sample data with pre-loaded example point clouds
 - **Public Sharing**: Generate and share live links to your visualizations
+- **MCP Server Support**: Can run as an MCP (Model Context Protocol) server for integration with other tools and agents
 
 ## Supported Formats
 
@@ -59,6 +60,24 @@ The following colormaps are available for elevation and fallback visualization:
 - **Max Points to Display**: Adjust the number of points displayed (50,000 to 2,000,000). Larger files are automatically subsampled for performance
 - **Example Files**: Load pre-packaged sample files to quickly explore the visualizer's capabilities
 
+## MCP Server Integration
+
+This application can function as an MCP (Model Context Protocol) server, allowing it to be integrated with AI agents and other tools. 
+
+To enable MCP server mode:
+
+1. **Via launch parameter:**
+```python
+demo.launch(mcp_server=True)
+```
+
+2. **Via environment variable:**
+```bash
+GRADIO_MCP_SERVER=True python app.py
+```
+
+When running as an MCP server, each API endpoint becomes available as an MCP tool that can be called by compatible clients and AI agents.
+
 ## Contributing
 
 We welcome contributions to improve this project. You can help by:

app.py

@@ -4,6 +4,12 @@ import laspy
 import trimesh
 import tempfile
 import os
+import warnings
+
+# Suppress asyncio warnings
+warnings.filterwarnings("ignore", category=ResourceWarning)
+import asyncio
+asyncio.set_event_loop_policy(asyncio.DefaultEventLoopPolicy())
 
 def load_laz(file_path):
     """Load LAZ/LAS file and return all data."""
@@ -264,4 +270,6 @@ with gr.Blocks(title="GeoSpatial-LiDAR-3D Point Cloud Visualizer") as demo:
     )
 
 if __name__ == "__main__":
-    demo.launch(ssr_mode=False)
+    # Launch with MCP server support for integration with other tools
+    # Can also set GRADIO_MCP_SERVER=True as environment variable
+    demo.launch(ssr_mode=False, mcp_server=True)