initial commit

.gitignore

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+venv

app.py

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+import gradio as gr
+from textblob import TextBlob
+
+
+def sentiment_analysis(text: str) -> dict:
+    """
+    Analyze the sentiment of the given text.
+
+    Args:
+        text (str): The text to analyze
+
+    Returns:
+        dict: A dictionary containing polarity, subjectivity, and assessment
+    """
+    blob = TextBlob(text)
+    sentiment = blob.sentiment
+
+    return {
+        # -1 (negative) to 1 (positive)
+        "polarity": round(sentiment.polarity, 2),
+        # 0 (objective) to 1 (subjective)
+        "subjectivity": round(sentiment.subjectivity, 2),
+        "assessment": "positive" if sentiment.polarity > 0 else "negative" if sentiment.polarity < 0 else "neutral"
+    }
+
+
+demo = gr.Interface(
+    fn=sentiment_analysis,
+    inputs=gr.Textbox(lines=2, placeholder="Text to analyze"),
+    outputs=gr.JSON(),
+    title="Sentiment Analysis",
+    description="Analyze the sentiment of the given text.",
+)
+
+
+if __name__ == "__main__":
+    demo.launch(mcp_server=True)

requirements.txt

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+gradio[mcp]
+textblob

xReadme.md

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+#Getting Started 
+
+mkdir mcp-sentiment
+cd mcp-sentiment
+python -m venv venv
+source venv/bin/activate  # On Windows: venv\Scripts\activate
+pip install "gradio[mcp]" textblob
+
+
+#Resources:
+https://huggingface.co/learn/mcp-course/unit2/gradio-server