Who actually paid
x402 payments on Base · 19 October 2026
concentrated In the last 24 h on Base, 659 x402 payments ($5.58) reached this seller’s wallet, from 11 wallets.
In the full record: the wallets that paid it, each with its payments, and the share the busiest three sent. How to get it: the $0.001 check over x402, Atlas Pro at $49 a month and for the seller itself, the Your buyers report at $29 a month.
Daily money · x402 USDC on Base · 13 Oct 2026 – 19 Oct 2026
13 Oct $14 (13 payers) · 14 Oct $12 (15 payers) · 15 Oct $10 (17 payers) · 16 Oct $5 (15 payers) · 17 Oct $12 (8 payers) · 18 Oct $5 (12 payers) · 19 Oct $6 (11 payers)
Relationships
x402 payments on Base · 12 October 2026 – 19 October 2026 · 8 days
46 buyers paid this seller over x402 on 8 of the window’s 8 days: 7,537 payments, $77.15. 12 of 46 buyers came back on another day (26%).
In the full record: its most loyal buyers, what is bought alongside it, who left it for whom, who came to it from where, and its early buyers, each with the counts behind it. How to get it: the $0.001 check over x402, Atlas Pro at $49 a month and for the seller itself, the Your buyers report at $29 a month.
Relationships are patterns in the x402 payments we observe on Base over the window: a buyer is a wallet that paid this seller’s payTo wallet, and came back means it paid on two or more different days. A wallet is not an agent, and a relationship is a pattern of payments, not a claim about who anyone is or who runs a wallet.
Is this your service? See who your buyers are: every wallet that paid you, day by day, and where the ones that left went, in one report.
Endpoints
The busiest of this seller’s 71 endpoints in the registry, by paid calls over 30 days; price and chain per endpoint.
| endpoint | paid calls | payers | price | chain |
|---|
/v1/tools/web-read | 11,859 | 15 | $0.002 | Base |
/v1/tools/search | 2,085 | 14 | $0.001 | Base |
/v1/tools/linkedin/profile-view | 623 | 3 | $0.01 | Base |
/v1/tools/research | 464 | 6 | $0.01 | Base |
/v1/tools/lookup/company-profile | 148 | 3 | $0.005 | Base |
/v1/tools/lookup/person-profile | 144 | 1 | $0.001 | Base |
/v1/tools/lookup/person-email-status | 98 | 4 | $0.001 | Base |
/v1/tools/lookup/person-email | 59 | 3 | $0.005 | Base |
/v1/tools/lookup/person-posts | 51 | 2 | $0.07 | Base |
/v1/tools/linkedin/reply | 48 | 4 | $0.02 | Base |
/v1/tools/email/send | 47 | 1 | $0.001 | Base |
/v1/tools/lookup/company-consumer-complaints | 14 | 2 | $0.005 | Base |
59 more endpoints not shown.
The replay
Paid calls, rolling 30 days · 12 October 2026 to 20 October 2026
2026-10-122026-10-20
Selling something like this
Matched automatically from each seller’s own short description. It will sometimes be wrong; tell us and we fix it.
| seller | paid calls | price | sells |
|---|
| qa.honeygate.app | 13 | $0.005–$0.12 | DOM to Markdown: extract readable content from a public HTML webpage |
| mach402.dev | 3 | $0.005 | Extract readable content from any URL as clean Markdown. Strips navigation, ads, footers. Returns title, autho |
| subnano.me | 4 | $0.56 | Read paid Subnano research and analysis as JSON with Markdown content. |
| x402-trends-server.onrender.com | 66 | $0.005–$0.05 | Scrape a public webpage and extract clean readable text. Use this web scraping endpoint when an AI agent needs |
| bytemine.pay.zeroclick.io | 5 | $0.01 | Read any company page in real time and return clean structured content, links, metadata, and the detected tech |
| puptra-pdf-snapshot.saastemly.com | 16 | $0.005 | The page's rendered content as Markdown. |
| api.language123.net | 9 | $0.001–$0.02 | URL to Markdown for LLM agents and RAG: send a web page or PDF link, get its main content as clean Markdown (t |
| x402-agent-api.onrender.com | 105 | $0.001–$0.08 | Read any public URL as clean Markdown for an LLM: articles, docs, product pages, news, PDFs (text by page), RS |
Going rate, the median of the 14 matched sellers with a listed price (of 14 matched): $0.009 a call. This seller’s endpoints run $0.001–$0.5, and the going rate falls inside that range — so no single over/under verdict is fair. Compare per endpoint.