Caddy plugin that charges AI crawlers real USDC to access your site

Hacker News

Hello, I built a Caddy middleware that implements the x402 protocol (by Coinbase) to charge AI crawlers real money for content access. When GPTBot, ClaudeBot, or any known AI crawler hits your site, it gets an HTTP 402 with payment requirements. If it pays (USDC on Base), it gets the content. If not, it gets nothing. Normal users are never affected. How it works: - Crawler detected by User-Agent → 402 response with price and wallet address - Crawler signs a USDC payment (EIP-3009) and retries with X-PAYMENT header - Plugin forwards to x402.org facilitator → on-chain settlement on Base - USDC goes directly from crawler's wallet to yours - Content served Configuration is a few lines in the Caddyfile: x402 { pay_to 0xYOUR_WALLET price 0.05 network base exempt /robots.txt } It's running on my site right now. No payments yet since most crawlers don't support x402, but they get blocked with a proper 402 instead of getting free content. When they do adopt it, the infrastructure is ready. Built with pure Go (no CGo), SQLite audit trail, Cloudflare-compatible headers.

Visit product View on Hacker NewsFeb 27, 2026

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Indie HackersFits the IH revenue-focused audience · Strong signals: compatible · Missing: supports, reddit linkedin, podcasting

84%84% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Product HuntOn track for Day 1 leaderboard · Strong signals: agent, claude, user · Missing: mac, agents, macos

62%62% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

47%47% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive

41%41% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: users · Missing: mobile apps, ios, personal

29%29% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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