NeuroFi Crypto Sentiment Analysis

x402

NeuroFi Crypto Sentiment Analysis is a paid API for AI agents from neurofi-chi.vercel.app, paid per call via x402, $0.5/call, status unknown (last checked 2026-09-15).

Returns AI-powered sentiment analysis for a given crypto topic using MiMo V2.5 LLM and live web search

Price / call$0.5

Seller volume →—

Success—

StatusUnknown

How this service works

NeuroFi provides AI-powered crypto intelligence endpoints covering token research, market analysis, contract auditing, sentiment tracking, news summarization, portfolio advice, deep research, text translation, language detection, SEO content generation, and contract explanation. All analytical endpoints require x402 micropayment on Base.

Output

A JSON object containing the queried topic and its AI-assessed sentiment label or score, e.g. {topic: 'bitcoin', sentiment: '...'}, powered by live web search and LLM analysis.

Example use cases

Example prompt

“What's the current market sentiment around Bitcoin right now — is it bullish, bearish, or neutral?”

Technical details

Endpoint

GEThttps://neurofi-chi.vercel.app/api/sentiment/%7Btopic%7D

When to prefer

Use this endpoint when you need real-time, AI-synthesized sentiment for a specific crypto asset or topic, especially when you want signals derived from live web content rather than static historical data. Prefer this over generic sentiment APIs when you need crypto-domain-specific analysis augmented by LLM reasoning.

Side effects

Unknown or unsupported topic returns empty or low-confidence sentiment
Tavily web search rate limit or unavailability causes degraded analysis
Payment not processed (402) returns no data
Malformed topic parameter returns error
LLM inference timeout on complex or trending topics

Input

{
  "topic": "Bitcoin"
}

Schema · Request body

Field	Type	Description
properties	string

Output

{
  "topic": "Bitcoin",
  "sources": [
    "https://scholarship.rollins.edu/honors/248",
    "https://www.mdpi.com/2306-5729/10/4/50",
    "https://pmc.ncbi.nlm.nih.gov/articles/PMC10174546",
    "https://pmc.ncbi.nlm.nih.gov/articles/PMC9581699",
    "https://ui.adsabs.harvard.edu/abs/arXiv:2204.10185"
  ],
  "sentiment": "1) **Sentiment Score**: 60 (Neutral to Slightly Bullish)  \nStudies confirm sentiment's strong influence on price, but current directional sentiment isn't measured. The score reflects acknowledged correlation, not a specific bullish or bearish consensus.\n\n2) **Key Themes**:  \n- Social media sentiment (e.g., Twitter) is a key predictor of Bitcoin price movements.\n- High correlation between sentiment shifts and price volatility/returns.\n- Advanced NLP models (BERT) are used for analysis.\n- Impact was notably studied during COVID-19.\n\n3) **Community Mood**: Analytically engaged, focused on data-driven prediction and the mechanics of sentiment impact.\n\n4) **Risk Factors**:  \n- **Sentiment Volatility**: Rapid shifts in social media mood can cause abrupt price swings.\n- **Predictive Uncertainty**: Models may fail during novel events or manipulation.\n- **Data Dependence**: Reliance on social media data can be biased or unrepresentative.",
  "timestamp": "2026-06-18T06:34:06.886Z",
  "searchResults": 5
}

Schema · Response

{
  "type": "json",
  "example": {
    "topic": "bitcoin",
    "sentiment": "..."
  }
}

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How this service works

Output

A JSON object containing the queried topic and its AI-assessed sentiment label or score, e.g. {topic: 'bitcoin', sentiment: '...'}, powered by live web search and LLM analysis.

Technical details

Endpoint

GEThttps://neurofi-chi.vercel.app/api/sentiment/%7Btopic%7D

When to prefer

Side effects

Unknown or unsupported topic returns empty or low-confidence sentiment
Tavily web search rate limit or unavailability causes degraded analysis
Payment not processed (402) returns no data
Malformed topic parameter returns error
LLM inference timeout on complex or trending topics

Input

{
  "topic": "Bitcoin"
}

Schema · Request body

Field	Type	Description
properties	string

Output

{
  "topic": "Bitcoin",
  "sources": [
    "https://scholarship.rollins.edu/honors/248",
    "https://www.mdpi.com/2306-5729/10/4/50",
    "https://pmc.ncbi.nlm.nih.gov/articles/PMC10174546",
    "https://pmc.ncbi.nlm.nih.gov/articles/PMC9581699",
    "https://ui.adsabs.harvard.edu/abs/arXiv:2204.10185"
  ],
  "sentiment": "1) **Sentiment Score**: 60 (Neutral to Slightly Bullish)  \nStudies confirm sentiment's strong influence on price, but current directional sentiment isn't measured. The score reflects acknowledged correlation, not a specific bullish or bearish consensus.\n\n2) **Key Themes**:  \n- Social media sentiment (e.g., Twitter) is a key predictor of Bitcoin price movements.\n- High correlation between sentiment shifts and price volatility/returns.\n- Advanced NLP models (BERT) are used for analysis.\n- Impact was notably studied during COVID-19.\n\n3) **Community Mood**: Analytically engaged, focused on data-driven prediction and the mechanics of sentiment impact.\n\n4) **Risk Factors**:  \n- **Sentiment Volatility**: Rapid shifts in social media mood can cause abrupt price swings.\n- **Predictive Uncertainty**: Models may fail during novel events or manipulation.\n- **Data Dependence**: Reliance on social media data can be biased or unrepresentative.",
  "timestamp": "2026-06-18T06:34:06.886Z",
  "searchResults": 5
}

Schema · Response

{
  "type": "json",
  "example": {
    "topic": "bitcoin",
    "sentiment": "..."
  }
}