Quickbrew.io Logo

QUICKBREW.IO: DATA ENDPOINTS FOR
AUTONOMOUS AGENTS.

Stop wasting LLM tokens on HTML garbage. We provide machine-to-machine data extraction, condensation, and sentiment analysis via the x402 payment protocol on the Base network.

buyer-agent.sh
# 1. Agent attempts request
> curl -i "https://api.quickbrew.io/condense?url=https://example.com"

HTTP/1.1 402 Payment Required
{"x402Version": 2, "error": "Payment required", "accepts": [{"network": "eip155:8453", ...}]}

# 2. Agent retries with EIP-712 Signature Payload
> curl -i "https://api.quickbrew.io/condense?url=https://example.com" \
       -H "PAYMENT-SIGNATURE: eyJmcm9tIjoiMHg2MzQx..."

HTTP/1.1 200 OK
{"condensed_text": "- Domain is used for documentation\n- No permission needed\n..."}

>> API_ENDPOINTS_CATALOG

Pay $0.001 to get the markdown. Pay $0.005 to get the bullets.

> /scrape

Clean Markdown Scraper

Strips HTML/CSS and returns raw, LLM-optimized Markdown text.

$0.001 USDC
> /condense

Context Condenser

Runs OpenAI OSS 20B directly at the edge to compress articles into dense bullet points.

$0.005 USDC
> /sentiment [BETA]

Experimental Extraction

Experimental endpoint for extracting factual claims and quotes. Accuracy not guaranteed.

$0.002 USDC

Integration Snippet

npm install quickbrew-node-client

import { QuickbrewClient } from "quickbrew-node-client";

// Initialize with your agent's Web3 private key
const client = new QuickbrewClient(process.env.AGENT_PRIVATE_KEY);

async function runAgent() {
  // 1. Autonomous Scrape (0.001 USDC)
  const data = await client.scrape("https://target-site.com");
  console.log(data.markdown);
}

Proof of Work