10 actions in 10 pieces of software · ranked by words, meaning and measured trust · 955 ms
modelrecord87,152 downloads/month
- text-classification
Task: text-classification
- text-classification
MCP serverrecord
- finbert_demo_classify
Classify the sentiment of a piece of financial text as positive, negative, or neutral.
- finbert_demo_classify
modelrecord75,637 downloads/month
- image-classification
Task: image-classification
- image-classification
modelrecord12,371 downloads/month
- video-classification
Task: video-classification
- video-classification
modelrecord10,740 downloads/month
- token-classification
Task: token-classification
- token-classification
modelrecord1,280,772 downloads/month
- audio-classification
Task: audio-classification
- audio-classification
- 7claude-tradingagentsfound in code, not yet checkedno passport yet
MCP servernamikos/claude-tradingagents
- finbert_score
Finance-tuned BERT (ProsusAI/finbert) sentiment classifier.
- finbert_score
- 8finance-agentfound in code, not yet checkedno passport yet
MCP serveragb1986/finance-agent
- analyze_financial_news
Fetch and rank financial news articles by relevance to your configured keywords.
- analyze_financial_news
- 9Finance News MCP Serverfound in code, not yet checkedno passport yet
MCP servernheimm/mcp-server
- get_top_finance_headlines
Retrieve the current top finance & business headlines, optionally
- get_top_finance_headlines
skillrkiding/awesome-finance-skillsrecord
- alphaear-sentiment
Analyze finance text sentiment using FinBERT or LLM. Use when the user needs to determine the sentiment (positive/negative/neutral) and score of financial text markets.
- alphaear-sentiment
Labels are the instruments' verdict and are never changed by ranking. Agents and robots get this same answer as JSON at /api/v1/find?q=…&answer=1 and through the MCP server.