Emotion Dataset Analysis MCP Server
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TDQS
Scored across 4 tools
The tools have mostly distinct purposes: analyze_emotion_distribution provides overall distribution, count_by_emotion counts specific emotions, get_sample retrieves random samples, and search_text finds text matches. However, analyze_emotion_distribution and count_by_emotion could potentially overlap in functionality since both provide emotion counts, though the former is comprehensive and the latter is specific.
All tool names follow a consistent verb_noun pattern using snake_case: analyze_emotion_distribution, count_by_emotion, get_sample, and search_text. The naming is predictable and readable throughout the set.
With 4 tools, the count is borderline for a dataset analysis server. It covers basic operations but feels thin for comprehensive analysis, lacking tools for filtering, updating, or advanced statistical analysis that might be expected in this domain.
The toolset covers core read operations (distribution analysis, counting, sampling, and searching) but has notable gaps. There are no tools for creating, updating, or deleting dataset entries, and missing advanced features like emotion trend analysis or dataset summarization limit completeness for the stated purpose.