10 actions in 10 pieces of software · ranked by words, meaning and measured trust · 633 ms

1. 1herbert-base-cased-sentimentverified and signedpassport

   modelrecord25,581 downloads/month

   • text-classification

     Task: text-classification

2. 2herbert-base-casedverified and signedpassport

   modelrecord139,896 downloads/month

   • feature-extraction

     Task: feature-extraction

3. 3bert-base-casedverified and signedpassport

   modelrecord3,586,597 downloads/month

   • fill-mask

     Task: fill-mask

4. 4bert-base-cased-squad2verified and signedpassport

   modelrecord62,134 downloads/month

   • question-answering

     Task: question-answering

5. 5xlnet-base-casedverified and signedpassport

   modelrecord161,323 downloads/month

   • text-generation

     Task: text-generation

6. 6distiluse-base-multilingual-casedverified and signedpassport

   modelrecord17,181 downloads/month

   • sentence-similarity

     Task: sentence-similarity

7. 7t5-base-indonesian-summarization-casedverified and signedpassport

   modelrecord10,113 downloads/month

   • summarization

     Task: summarization

8. 8tiny-distilbert-base-caseddemo or tutorialno passport yet

   modelrecord25,501 downloads/month

   • token-classification

     Task: token-classification

9. 9io.github.CSOAI-ORG/sentiment-analysis-ai-mcpfound in code, not yet checkedno passport yet
   • analyze_sentiment

     Analyse the sentiment of a text. Returns score (0-1), label (positive/negative/neutral/mixed), and confidence.

10. 10Zero-Sentiment-0.2Mdemo or tutorialno passport yet

    MCP serverrecord

    • zero_sentiment_0_2m_demo_classify

      Classify the sentiment of a text snippet as negative, neutral, or positive. Returns: Mapping of each sentiment class to its confidence in [0, 1].