from fastmcp import FastMCP
from textblob import TextBlob
mcp = FastMCP("SentimentTools")
@mcp.tool()
def analyze_sentiment(text: str) -> dict:
"""Analyze the sentiment of provided text.
This function uses TextBlob to determine the emotional tone of the input text.
It evaluates both polarity (positive/negative) and subjectivity (objective/subjective).
Args:
text: The input text string to analyze for sentiment
Returns:
dict: A dictionary containing:
- polarity: Float between -1.0 (negative) and 1.0 (positive)
- subjectivity: Float between 0.0 (objective) and 1.0 (subjective)
- assessment: String classification ("positive", "negative", or "neutral")
"""
blob = TextBlob(text)
# Access sentiment properties (bypassing type checking issues)
sentiment_obj = blob.sentiment
polarity = getattr(sentiment_obj, "polarity")
subjectivity = getattr(sentiment_obj, "subjectivity")
assessment = (
"positive" if polarity > 0 else "negative" if polarity < 0 else "neutral"
)
return {
"polarity": polarity,
"subjectivity": subjectivity,
"assessment": assessment,
}
if __name__ == "__main__":
mcp.run(transport="stdio", show_banner=False)
