Emotion Dataset Analysis MCP Server

Instructions

Implementation Reference

• server.py:144-167 (handler)

  The implementation of the analyze_emotion_distribution tool, which calculates emotion distribution from a dataset.

  def analyze_emotion_distribution() -> str:
      """Get the distribution of emotions in the dataset.
  
      Returns:
          JSON string with counts and percentages for each emotion
      """
      dataset = get_dataset()
  
      counter = Counter(sample["label"] for sample in dataset)
      total = len(dataset)
  
      distribution = []
      for label_id, count in counter.most_common():
          distribution.append({
              "emotion": EMOTION_LABELS[label_id],
              "count": count,
              "percentage": round((count / total) * 100, 2)
          })
  
      return json.dumps({
          "total_samples": total,
          "distribution": distribution
      }, indent=2)

• server.py:143-143 (registration)

  MCP tool registration for analyze_emotion_distribution.

  @mcp.tool()