Any website, in one minute, into a tool AI can use directly
No scrapers to write, no APIs to maintain, no fear of site redesigns. Create once and get REST API, MCP, CLI, RSS and SDK together.
Five ways to call, one website
One capability, five ways to connect, into any workflow you already have
REST API
Each data capability gets its own REST endpoint returning structured JSON, with an OpenAPI description ready to wire into your systems.
MCP tools
Built on the stateless architecture of the MCP 2026-07-28 release candidate, so Claude and other assistants can discover and call your data. Compatibility will be verified once the spec is final.
CLI
Create endpoints, check status, and fetch data entirely from the terminal. --json output pipes straight into shells, scripts, and AI agents.
RSS feeds
Every data capability can emit a standard RSS feed. Subscribe to site changes from your usual reader, automation tool, or notification service, no code required.
Official SDKs
Official Python and JavaScript SDKs let you connect in a few lines, with full typing and error handling. Scraping still runs in the cloud; no source code is shipped.
Not just fetching, we watch for changes
Data quality and content changes, guarded for you automatically
Data quality guard
When a site changes, most tools silently return broken data. We run schema-drift detection on every call and alert honestly when fields disappear.
Change detection
Beyond turning sites into APIs: we watch them for you. Every run diffs against the last snapshot; additions and removals push instantly via signed webhooks.
Auto scheduling
Set an auto-fetch interval per capability, as often as every five minutes, with timezone display and an immediate first run on save, so your data is always fresh.
Quality repair pipeline
When a source site changes and breaks a fetch, the system classifies the failure, generates repair candidates, and tests them in a sandbox before applying, minimizing maintenance.
Let AI read your data directly
Ask questions about site data using your own model
Dataflow chat (BYOK)
Bring your own model key (OpenAI, Anthropic, or Google) and ask questions directly about a capability's data. Keys are encrypted; your data goes only to your own model.
Deploy and localize on your terms
Where data lives, how it's formatted, who can access, your call
Self-hosted
One-command Docker Compose deploy. Your data stays on your machines; license keys verify offline.
Taiwan-native cleanup
Optionally normalize formats common on Taiwanese sites: ROC-era dates to ISO, full-width characters to half-width, comma-separated numbers to numeric.
Team seats
Invite teammates to share one license. They sign in with their own accounts and inherit the plan automatically, ideal for organizations managing capabilities together.
Five use cases, one engine
The same fetch → quality-guard → change-detection engine. Point it at a different site and you have a new use case. The regulatory and awards data below was actually scraped.
If the world has a billion AI agents, through whom will they reach external capabilities?
How they used to struggle, how easy it is now
The following are typical scenarios across industries. Real customer feedback is being collected and will be published with consent.
You might not believe it, but we used to monitor websites on a rotating shift. Three of us took turns, and the first thing every morning was opening the regulator's notice pages and a dozen competitors' rate pages one by one, screenshotting, pasting into a shared sheet, marking what changed in red. The scariest part was when someone was off or missed something; we'd only realize the numbers didn't add up when the monthly report was done, then trace back which notice changed on which day. That backward hunt was crushing. Now all these pages are on auto-monitoring; the moment anything changes, the alert lands in our group chat. Nobody patrols by hand anymore. The biggest change is that the anxiety of 'did we miss something again' is gone, and the team is freed from screen-watching to do analysis that actually needs judgment.
Anyone in e-commerce knows your rival's price is your lifeline. I used to hire a part-timer just to screenshot twenty-plus competitor pages every morning into an Excel sheet, marking price cuts and restocks. The problem is people get tired and miss things; sometimes a rival quietly changed a price at noon and we'd find out the next day, losing a whole campaign's volume. And when the part-timer quit, I had to retrain the whole process. Now I've turned competitor pages into APIs that diff automatically every day. The moment a price moves, the system computes the difference and pushes it to me, down to the percentage change and exactly when stock went from in to out. Pricing used to be gut feeling plus luck; now it's decisions backed by data, and it feels so much more solid.
On Shopee, identical products get cut to the bone. Who's gaming rankings, who's piggybacking, who quietly changed a price at midnight; if you're not watching, you get eaten. My old method was crude: Shopee open on my phone, scrolling whenever I had a moment, screenshotting rivals into notes, organizing at night. It got to the point I was scrolling rival shops before bed and my family said I was obsessed. What really broke me was that despite all that effort, I'd still miss things, because no one can watch 24 hours a day. Now I've organized the shops and keywords I follow into a data stream; ranking changes and new rivals get logged automatically, and I open up to a complete change history. Selection and pricing finally have a basis, and I can sleep at night instead of scrolling until dawn.
Ten years of contract work, and the thing I least want to touch, hands down, is scrapers. A client wants data, so I write a scraper, and the nightmare begins. The target site changes its layout and the whole thing breaks, usually discovered when the client reports the data looks off, then I'm up all night fixing it. Worse is anti-scraping: captchas, IP blocks, dynamic loading, every gate costs time to get around. The hidden cost of maintaining a scraper far exceeds the original quote; the more you do, the more you lose. After using this, the world went quiet. I hit their REST directly, or install the SDK and it's three lines of code, and I get clean JSON. If the structure breaks it alerts me proactively; I even know about a site redesign before the client does. It's like outsourcing the most annoying, most draining part entirely, so I can focus on real product logic. Contract work just feels different now.
In import-export, information is money. Exchange rates, commodity quotes, customs notices, regulatory updates from various countries, all scattered across a dozen sites. Just gathering them every morning ate up half a colleague's morning. He'd open a pile of tabs, copy them one by one into a report, and by the time he finished it was nearly noon, but the client's price inquiries had already come in. All we could say was 'let me check', and in that back-and-forth, the fast orders got taken by quicker-reacting competitors. Now all these sources are consolidated into one data output; we get the latest quotes and notices in one go, and no one has to be a human transcriber. When a client asks for a price, I can quote on the spot. That confidence of always having the latest numbers at hand is, for anyone doing business, the difference between closing and losing a deal.
Anyone running a clinic knows that health insurance reimbursement rules and Ministry of Health regulations change, and no one calls to tell you when they do. A small clinic like ours has no one dedicated to watching these notices; we used to have admin staff check the ministry and insurance bureau sites when they had time, but everyone's swamped just handling patients, so it easily got put off. The worst case is a rule changes without our knowing, we file the old way, get the claim denied, and then lose the money and spend time appealing. That kind of unfairness is the most disheartening. Now I've set the relevant notice pages on auto-tracking; the moment there's an update, the alert comes, and staff don't have to periodically check sites. For us, we handle the medical expertise well, but having one less place administratively where things can go wrong means a little more peace of mind, and a little less unnecessary loss.
More real customer stories, being collected and published
Who uses which exit
One dataset, five ways to reach it. The difference is not technical: it is how your team already works.
Regulatory tracking at a bank
Compliance staff must check daily whether the regulator issued a new order or amended an existing rule. Doing that by hand means one missed item can mean a fine. Turn the regulator's announcement page into an API, feed it into the internal compliance system, and let managers simply ask an AI assistant what changed this week.
Why this exit
MCP lets non-technical compliance leads query directly; the API puts the same data into internal systems with an audit trail. Both read the same source, so there is no version drift.
FAQ
No. Sites with clear structure and public content work best. We do not bypass technical protection such as Cloudflare or DataDome: those are honestly blocked. Where robots.txt disallows crawling, we warn you; if you own the site or hold written permission, you may proceed after making a declaration, which we log. Do not proceed without legal authority.