Less Token,More Context.
Attention0 curates high-quality, time-series data from social media and developer platforms — daily snapshots, historical trends, and valuable signals served as plain .md files. Addressable by URL, ready for any AI agent.
$ curl youtube.com/@mrbeast
~84,291 chars<!DOCTYPE html>
<html lang="en"><head><meta charset="utf-8">
<meta name="viewport" content="width=device-width, initial-scale=1">
<title>MrBeast - YouTube</title>
<meta name="description" content="SUBSCRIBE FOR A COOKIE">
<script nonce="Wb2kXA">(function(){var g=this||self;var h,k=[];
function l(a){for(var b;b=k.shift();)b(a)};window.ytcfg.set=
function(a,b){var f=window.ytcfg.data_=window.ytcfg.data_||{};
if(typeof a==="object")for(var d in a)a.hasOwnProperty(d)&&
(f[d]=a[d]);l(window.ytcfg)})();</script>
<link rel="preload" as="script" href="/s/desktop/5a21b84d/base.js">
<link rel="preload" as="script" href="/s/desktop/5a21b84d/www-i18n.js">
<style>html{scrollbar-color:auto}body,html{height:100%;margin:0}
#container{display:flex;flex-direction:column;position:fixed;
bottom:0;left:0;right:0;top:0}ytd-app{display:flex;height:100%}
</style><script>var ytInitialData={"responseContext":{
"serviceTrackingParams":[{"service":"CSI","params":[{"key":
"yt_li","value":"1"},{"key":"c","value":"WEB"},{"key":"cver",
"value":"2.20250408.00.00"}]},{"service":"GFEEDBACK","params":
[{"key":"browse_id","value":"UCX6OQ3DkfWmd9Do..."}]}]},
"header":{"pageHeaderRenderer":{"content":{"pageHeaderViewModel":
{"title":{"dynamicTextViewModel":{"text":{"content":"MrBeast"}}}
,"image":{"decoratedAvatarViewModel":{"avatar":{"avatarViewModel":
{"image":{"sources":[{"url":"https://yt3.googleusercontent.com/...
...[+84,291 lines]
8 Platforms. One URL pattern.
Every data source is accessible at attention0.com/{platform}/{handle}.md
/youtube/@mrbeast.md/tiktok/@charlidamelio.md/sora/featured.md/github/vercel/next.js.md/discord/supabase.md/patreon/kurzgesagt.md/skool/alex-hormozi.md/ranks/vercel.com.mdHow it works
Three steps from raw web to agent-ready context.
Our workers monitor YouTube, GitHub, TikTok, and 5 more platforms every 24 hours — building time-series snapshots of profiles, stats, content metadata, and engagement trends.
Raw HTML and API responses are parsed, normalized, and structured. No noise, no duplicates — just the signal your agent needs.
Clean data lands in a plain .md file at a predictable URL. Fetch it with curl, include it in a prompt, or pipe it into your RAG pipeline.
Built for agents & humans alike
Any tool that can fetch a URL can use Attention0.
- Track competitor channel growth weekly
- Feed creator profiles into an LLM for trend analysis
- Monitor open-source repo star velocity
- Build domain rank change alerts
- Power a Slack bot with daily social signal digests
- Provide up-to-date context in RAG pipelines
- Research influencer audiences without scraping yourself
- Compare Patreon tier pricing across creators
// Give your agent fresh context — no scraping needed
const url =
"https://attention0.com/youtube/@mrbeast.md";
const res = await fetch(url);
const context = await res.text();
const response = await anthropic.messages.create({
model: "claude-opus-4-5",
max_tokens: 1024,
messages: [
{
role: "user",
content: `Here is the latest data:\n\n${context}
\nSummarize key trends.`,
},
],
});Power your next agent
Start fetching curated social and developer signals in minutes. No setup, no API keys, no rate limit headaches.