creating first version of sentiment Mcp server

.gitignore

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+# Python-generated files
+__pycache__/
+*.py[oc]
+build/
+dist/
+wheels/
+*.egg-info
+
+# Virtual environments
+.venv

.python-version

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+3.10

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 {
+        "polarity": round(sentiment.polarity, 2),  # -1 (negative) to 1 (positive)
+        "subjectivity": round(sentiment.subjectivity, 2),  # 0 (objective) to 1 (subjective)
+        "assessment": "positive" if sentiment.polarity > 0 else "negative" if sentiment.polarity < 0 else "neutral"
+    }
+
+# Create the Gradio interface
+demo = gr.Interface(
+    fn=sentiment_analysis,
+    inputs=gr.Textbox(placeholder="Enter text to analyze..."),
+    outputs=gr.JSON(),
+    title="Text Sentiment Analysis",
+    description="Analyze the sentiment of text using TextBlob"
+)
+
+# Launch the interface and MCP server
+if __name__ == "__main__":
+    demo.launch(mcp_server=True)

flagged/log.csv

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+text,output,flag,username,timestamp
+,,,,2025-05-31 17:03:57.524285
+,,,,2025-05-31 17:03:58.469761

main.py

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+def main():
+    print("Hello from mcp-sentiment!")
+
+
+if __name__ == "__main__":
+    main()

pyproject.toml

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+[project]
+name = "mcp-sentiment"
+version = "0.1.0"
+description = "Add your description here"
+readme = "README.md"
+requires-python = ">=3.10"
+dependencies = [
+    "gradio[mcp]>=5.32.0",
+    "textblob>=0.19.0",
+]

requirements.txt

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+gradio[mcp]>=5.32.0
+textblob>=0.19.0