Initial commit

.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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+3.12

app.py

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+import json
+import gradio as gr
+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
+    """
+    blob = TextBlob(text)
+    sentiment = blob.sentiment
+
+    result = {
+        # -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"
+    }
+
+    return json.dumps(result)
+
+
+# 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()
+    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)

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 = ">=3.12"
+dependencies = []

requirements.txt

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+gradio[mcp]
+textblob