Update app.py

app.py

@@ -1,14 +1,15 @@
 import json
 import gradio as gr
+from gradio_mcp import enable_mcp
 from textblob import TextBlob
 
 def sentiment_analysis(text: str) -> str:
     """
     Analyze the sentiment of the given text.
-
+    
     Args:
         text (str): The text to analyze
-
+        
     Returns:
         str: A JSON string containing polarity, subjectivity, and assessment
     """
@@ -20,18 +21,41 @@ def sentiment_analysis(text: str) -> str:
         "subjectivity": round(sentiment.subjectivity, 2),  # 0 (objective) to 1 (subjective)
         "assessment": "positive" if sentiment.polarity > 0 else "negative" if sentiment.polarity < 0 else "neutral"
     }
-
-    return json.dumps(result)
+    
+    return json.dumps(result, indent=2)
 
 # Create the Gradio interface
 demo = gr.Interface(
     fn=sentiment_analysis,
     inputs=gr.Textbox(placeholder="Enter text to analyze..."),
-    outputs=gr.Textbox(),  # Changed from gr.JSON() to gr.Textbox()
+    outputs=gr.Textbox(),
     title="Text Sentiment Analysis",
     description="Analyze the sentiment of text using TextBlob"
 )
 
-# Launch the interface and MCP server
+# Enable MCP server with proper configuration
+mcp_server = enable_mcp(
+    demo,
+    tool_config={
+        "sentiment_analysis": {
+            "description": "Analyze the sentiment of the given text. Returns polarity (-1 to 1), subjectivity (0 to 1), and overall assessment (positive/negative/neutral).",
+            "parameters": {
+                "type": "object",
+                "properties": {
+                    "text": {
+                        "type": "string",
+                        "description": "The text to analyze for sentiment"
+                    }
+                },
+                "required": ["text"]
+            }
+        }
+    }
+)
+
+# Launch the interface
 if __name__ == "__main__":
-    demo.launch(mcp_server=True)
+    demo.launch(
+        server_name="0.0.0.0",
+        server_port=7860
+    )