x402 APIs - Text Summarization is a paid API for AI agents from x402-apis-eta.vercel.app, paid per call via x402, $0.01/call, not verified (last probed 2026-10-30); live alternatives: GPT-5.5 Text Summarization Tool ($0.0029) and x402node Text Summarizer ($0.005).
Agents call it through Zero, which pays per call: no API key and no wallet of your own. New accounts start with $5. Live alternatives for the same use case: GPT-5.5 Text Summarization Tool ($0.0029) · x402node Text Summarizer ($0.005).
Summarizes a given text into a concise set of sentences using pay-per-request micropayments via the x402 protocol
AI-agent-friendly APIs with instant micropayments via x402 protocol. No API keys, no accounts - just pay and access.
A condensed summary of the provided text, reduced to the requested number of sentences (or a default number if max_sentences is not specified), capturing the key points of the original content.
POSThttps://x402-apis-eta.vercel.app/api/summarize?utm_source=zero.xyzChoose this endpoint when you need quick, on-demand text summarization without setting up API keys or accounts, and when you are operating in an x402-compatible micropayment environment. It is well-suited for AI agents that need to condense large amounts of text programmatically and can pay $0.01 USDC per call. Ideal for Coinbase/x402 ecosystem integrations.
{
"text": "Artificial intelligence is transforming industries worldwide. Companies are investing billions in machine learning research. Governments are beginning to regulate AI development to ensure safety and fairness. Experts predict AI will reshape the labor market over the next decade.",
"max_sentences": 3
}| Field | Type | Description |
|---|---|---|
| textrequired | string | |
| max_sentences | number |
{
"summary": "Artificial intelligence is transforming industries worldwide. Companies are investing billions in machine learning research. Governments are beginning to regulate AI development to ensure safety and fairness.",
"keywords": [
"artificial",
"intelligence",
"transforming",
"industries",
"worldwide",
"companies",
"investing",
"billions",
"machine",
"learning"
],
"summarized_at": "2026-06-18T06:16:43.678Z",
"summary_length": 208,
"original_length": 279,
"compression_ratio": "25%"
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