The leading web data infrastructure company, Decodo, has launched a Web Data API that combines scraping, search, mapping, and crawling into a single subscription. The release brings together capabilities that AI teams previously had to source from separate vendors, each with its own integration and its own authentication.
The Web Data API brings scraping, search, mapping, and crawling together as four capabilities behind a single key. That means an agent can discover a site’s structure first, decide what is worth pulling, and act on that decision using the same authentication throughout, rather than fetching one page at a time with no sense of what else is on the site.
To showcase the full potential of this new solution, Decodo is opening access with a free tier of up to 10,000 requests a month across all four capabilities, with no credit card required to start, a wider allowance than most competing scraping APIs offer at no cost.
Why agents keep failing on the live web
An AI agent that can reason well and still gets basic facts wrong often has a simple root cause – the page it needed was never reached. A model can plan a task correctly and decide it needs to check a price, a schedule, or a policy page. Then the request runs into a CAPTCHA, a rate limit, or a layout the parser doesn’t recognize. The worst of these failures don’t look like failures: the response comes back looking like a normal page, so the agent never learns anything went wrong and answers from whatever it already knew from training.
Most agent frameworks wire in a single search tool and treat that as solved, but search alone rarely covers what an agent is being asked to do. Checking whether a claim on a company’s own site is still current, comparing listings across a handful of competitor pages, or pulling the full text of a document referenced in a search result all require getting past the same defenses a browser encounters, and most tool-calling setups were never built to handle that. The web access layer is often the least tested part of an agent stack.
Four capabilities behind one key
The Web Data API gives an agent four things to call through a single key:
- Scrape endpoint pulls clean content from a single page, even behind anti-bot protection, and is suited to checking one fact or one listing.
- Search endpoint returns live web results in place of a static index, useful when an agent needs to find something rather than fetch something it already has a link to.
- Map endpoint discovers a site’s structure without pulling every page on it, which lets an agent scope a target before deciding what is worth the cost of a full crawl.
- Crawl endpoint then follows links automatically and pulls the pages that the /map identified as relevant, up to 10,000 in a single job.
Results come back in HTML, JSON, CSV, or Markdown, which matters more to an agent pipeline than it might look. A tool-calling agent typically wants JSON it can parse directly into a function response, while a pipeline feeding a retrieval index wants Markdown it can chunk and embed without extra cleanup. Getting the format right at the source removes a conversion step that would otherwise sit between the API and whatever the agent does next. An agent that has to convert every response before it can use it is doing extra work on every single call, which adds latency to a task the user is waiting on.
Vaidotas Juknys, CEO at Decodo, noted, “When a scrape request fails, an agent generally has no way to detect that on its own, so it answers from training data instead of flagging an error. Search and map help an agent find the right, current page, and scrape pulls its content even when the site pushes back, so the agent answers from what’s actually there.”
The infrastructure an agent is calling
Underneath the four endpoints is a proxy network. Developers and teams building web data projects can leverage 125+ million residential, ISP, mobile, and datacenter IP addresses across 195+ locations for worry-free publicly available data collection. Every capability in the Web Data API, including a large crawl job, draws on that same pool and inherits the same rotation and retry logic that keeps a request from getting blocked halfway through.
A single map call can surface up to 147K URLs, which is enough to describe the structure of most corporate sites, documentation hubs, or product catalogs without a second call. For an agent deciding what to crawl, that scope check costs a fraction of what a full crawl would, and it means the agent can make that decision with real information about a site rather than guessing how large it might be.
Getting an agent connected
Testing the Web Data API doesn’t require a credit card, and the free tier itself is unusually wide: several of the most widely used competing scraping APIs cap free access somewhere between 1,000 and 5,000 requests a month, enough to run a short demo but not much beyond it. A developer building an agent can run it against a real target site, not a sample one, before deciding whether the API fits the agent’s tool stack at all.
Signing up asks for little more than an email address and returns an active key immediately, so a developer can wire the API into an agent’s tool definitions within minutes rather than waiting on a sales conversation. The same key that works during that first test continues to work as usage grows, since scrape, search, map, and crawl all sit behind one authentication path rather than four separate ones an agent would otherwise need to manage.
“Most of the agent teams we see on our scraping infrastructure start with a handful of tool calls during a weekend project and reach thousands of requests a day within a few months of moving to production. The way the agent calls the API stays the same throughout that growth. Usage and billing are what scale, not the integration itself,” Vaidotas Juknys added.
Where AI teams are putting agents to work
A customer support agent can scrape a company’s own policy pages before answering a question about pricing or a return window, instead of relying on whatever was true when the model was last trained. A shopping agent comparing options across several retailers can map each site to find the categories it covers, then crawl just those on a regular schedule. When a user asks, it answers from fresh listings rather than pulling entire catalogs it has no use for.
A research agent summarizing a fast-moving story can search for the latest coverage, scrape the two or three most relevant articles, and cite what it read instead of reconstructing the story from headlines a search snippet already cut short.
In each case, the API works as a tool the agent calls mid-task or on a schedule, not a separate system a developer has to build and maintain alongside the agent itself. Testing it costs nothing to start – the free tier covers all four capabilities, and a developer can have a working key within minutes of deciding to test-drive the Web Data API.
