News Sentiment Analysis

x402

News Sentiment Analysis is a paid API for AI agents from agentsvc.io, paid per call via x402, $0.006/call, status unknown (last checked 2026-10-11).

Analyzes recent news sentiment for a company, token, person, or topic using AI-powered summaries across GDELT and Hacker News sources

Price / call$0.006

Seller volume →—

Success—

StatusUnknown

How this service works

86 APIs for AI agents: web scraping and crawling to Markdown, AI summaries, data extraction and cited answers, screenshots and PDF, PDF, OCR and document conversion, news, paper and developer search and more, paid per call with USDC on Base, Solana, Polygon or Arbitrum via x402. No account, no API key, free sample on every service.

Output

Returns a JSON object with: an overall sentiment label (e.g. 'mixed'), a numeric sentiment score, per-article sentiment classifications (positive/neutral/negative) with URLs and publication dates, an aggregate count of positive/neutral/negative articles, a list of dominant themes, an AI-generated prose summary of the coverage, the AI model used (Claude Haiku), and the news index window (last 7 days, sourced from GDELT and Hacker News).

Example use cases

Crypto token sentiment check

“What's the current news sentiment around Ethereum? Grab 15 articles from the tech category and tell me whether coverage is mostly positive, negative, or mixed, and what the main themes are.”

Pre-earnings press coverage check

“Before our call today, can you check how Siemens is being covered in business news? Get up to 20 articles and give me a sentiment score, the overall vibe, and the key topics being discussed.”

Health topic media monitoring

“How is the press covering Ozempic in health news right now? Pull 10 articles and tell me the sentiment breakdown and what themes are dominating the coverage.”

Technical details

Endpoint

POSThttps://agentsvc.io/api/v1/proxy/news-sentiment?utm_source=zero.xyz

When to prefer

Choose this endpoint when you need AI-summarized, multi-article sentiment analysis for a named entity (company, token, person, or topic) sourced from a curated news index (GDELT + Hacker News), returned as a single structured payload with themes and counts — rather than raw article search or social media sentiment. It is best suited for financial research, competitive monitoring, and pre-briefing workflows where a quick, cited sentiment snapshot is more useful than a raw feed.

Side effects

Unknown or very niche topic returns sparse results with few articles
Topic string too ambiguous may return irrelevant articles from unrelated entities with same name
Payment failure via x402 if USDC balance is insufficient or wrong chain
Rate limiting or upstream index unavailability may cause delayed or empty responses
Category filter may exclude relevant coverage if topic spans multiple domains

Input

Schema · Request body

Field	Type	Description
limit	integer
topic	string	Company, token, person or topic, e.g. Bitcoin or Siemens
category	string

Output

Schema · Response

{
  "type": "json",
  "example": {
    "data": {
      "model": "claude-haiku-5-5",
      "score": 0.1,
      "topic": "Bitcoin",
      "counts": {
        "neutral": 5,
        "negative": 1,
        "positive": 2
      },
      "themes": [
        "price volatility and technical levels"
      ],
      "window": "last 7 days, our news index (GDELT and Hacker News)",
      "overall": "mixed",
      "summary": "Coverage of Bitcoin is split between price-technical analysis showing uncerta...",
      "articles": [
        {
          "url": "https://economictimes.indiatimes.com/news/international/us/bitcoins-four-mont...",
          "title": "Bitcoin BTC USD price analysis: Bitcoin's four-month higher-low pattern expla...",
          "source": "indiatimes.com",
          "sentiment": "neutral",
          "published_at": "2026-10-09T21:30:00.000Z"
        }
      ],
      "analysed_at": "2026-10-10T10:12:15.017Z"
    },
    "success": true
  }
}

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