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An AI agent is software that uses tools to pursue a task for a user. To work with online information, an agent may search for pages, fetch a known URL, query an API, or operate a browser. The language model alone does not guarantee internet access: the agent’s application determines which tools it can use and supplies retrieved information to the model.
What is an AI agent?
An AI agent combines a model—often a language model—with software that lets it take steps toward a goal. Those steps can include choosing a tool, sending it a request, interpreting the result, and deciding what to do next. For an online task, that might mean finding relevant pages, opening one, extracting information, or carrying out an action through a website or service.
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This is different from asking a model to answer from text already included in a prompt. A model cannot see a live webpage just because it is a language model. It needs an application that gives it an appropriate search, fetch, API, or browser tool and passes back the resulting information. The application also determines what permissions the tool has and which parts of its results the model receives.
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The World Wide Web Consortium’s 8 July 2026 Group Note describes software that interacts with websites for a user as a web user agent. Its definition includes software that renders website content as well as software that performs actions requested or authorized by a user. That framing helps explain why an AI system can be a web user agent without being a conventional human-operated browser.
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How does an AI agent get information from a website?
The access path depends on the task and the tools the application makes available. Searching, fetching, calling an API, and operating a browser are related, but they are not interchangeable. A task may use one route or combine several.
- Interpret the request. The application gives the model the user’s goal and any relevant context. The model can then select from the tools it has been offered; it cannot select a capability the application has not provided.
- Use a tool to retrieve or act on information. A search tool can discover candidate pages, a fetch tool can retrieve a known URL, an API can exchange structured data, and a browser can inspect and interact with a rendered page.
- Return tool results to the model. The application passes back some or all of the information the tool retrieved. The model uses those results to respond, choose another step, or request another tool action.
- Stop or continue according to the task. A one-step lookup may need only a result. A multi-step workflow may require additional searches, page visits, API calls, or browser interactions.
This is a description of the general pattern, not a promise that every product follows the same implementation. Applications differ in their tools, permissions, the information they return, and the actions they allow.
Which methods can agents use to access online content?
| Method | What it does | Best fit | Important limitation |
|---|---|---|---|
| Search | Finds candidate pages in response to a query. | Discovering sources when the agent does not already know which URL to read. | Finding a page is not the same as retrieving all of its content or completing an action on it. |
| Fetch | Reads content from a known URL or document. | Retrieving a particular page once its address is known. | It does not perform the discovery role of search; what it can return depends on the fetch tool and the page. |
| API | Sends structured requests to a service and receives structured responses. | Accessing service data or functions through an interface designed for software. | A suitable API must exist, and the agent must have access to it. It may not expose every page or workflow a user can access in a browser. |
| Browser automation | Uses a browser to navigate, inspect rendered content, and interact with a page. | Working with rendered pages or tasks that require navigation and interaction. | Browser access can be limited by permissions, login requirements, page behavior, or the browser tool’s capabilities. |
| Hybrid access | Combines methods, such as using an API for structured data and a browser for a workflow. | Tasks for which no single route provides all the information or interactions needed. | It still depends on the availability and permissions of each tool used. |
Search discovers; fetch retrieves
A search tool is useful when the agent needs to locate possible sources. An OpenAI web-search tool, for example, is documented with live, cached, and disabled modes. Those modes affect whether the tool can use live search or cached information, or is unavailable; the presence of a language model does not determine which mode an application has enabled.
Fetching serves a different purpose: it reads a page or document at an address the agent already has. Cloudflare’s Agents documentation distinguishes fetching from search for this reason. A workflow might search for an official help page and then fetch that known page, but a fetch tool alone is not a general-purpose way to discover relevant sites.
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APIs provide structured access
An API is a machine-oriented interface to a service or its data. Instead of trying to infer meaning from a page’s layout, an agent can send a structured request and receive a structured response. When an appropriate API is available and authorized, this can be a more direct way to work with the information or functions it exposes.
That does not make an API universally preferable. It only provides access to the service’s exposed interface, and the agent needs the relevant access. If the task involves information or an interaction that the API does not provide, another route may be needed.
Browsers handle rendered pages and interactions
A browser tool can navigate a page and inspect its rendered state. This matters when the content depends on JavaScript or when the task requires interacting with a page rather than merely reading a known document. Cloudflare describes browser tools that can read DOM state, evaluate JavaScript, capture screenshots, and interact through the Chrome DevTools Protocol.
These capabilities describe a class of browser tooling, not a guarantee that every agent has each capability. A browser tool may have a narrower scope, and a page may still require a login, a user interaction, or a permission the tool does not possess.
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Hybrid access uses more than one route
A hybrid agent can use an API where structured data is available and a browser where it needs rendered content or a workflow the API does not expose. This is not merely a theoretical distinction: a 2025 Findings of ACL paper compared API-based, browsing, and hybrid web agents on the WebArena benchmark. In that study, API-based agents outperformed browser-only agents in the reported experiments, and hybrid agents outperformed both approaches across nearly all of the study’s tasks.
Can an AI agent browse the internet?
Some can, if their application provides a suitable tool and enables it. “Browse the internet” can mean several different things: searching for current pages, fetching a known address, inspecting a rendered page, or interacting with a website. An agent with search enabled may discover sources without being able to operate a browser; an agent with a browser tool may be able to inspect pages but still lack broad search access.
Access can also be bounded by the application’s settings and the target site. A page may require authentication or interaction, and a tool may have only limited permissions or return selected content rather than the entire page. A search result, a fetched document, and a browser view are therefore not necessarily equivalent representations of a site.
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Can AI agents read JavaScript websites?
They may be able to, but the answer depends on the access method. A fetch tool may return a page or document without providing the same rendered experience a browser would. A browser automation tool can inspect rendered state and may handle content that depends on JavaScript. The browser capabilities documented by Cloudflare—such as reading DOM state and evaluating JavaScript—illustrate how such access can work.
JavaScript rendering is only one part of access. The page may still depend on interaction, login, or permissions that the agent’s browser tool cannot provide. Conversely, if the needed information is exposed through a suitable API, a browser may not be necessary. The useful question is not simply whether a site uses JavaScript, but whether the available tool can retrieve the information or complete the interaction the task requires.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How should you choose between an API, browser, and search?
Choose based on the shape of the task, not on a broad assumption that one method is always best. These checks help identify a sensible route:
- Is the target already known? If the agent has a specific URL, a fetch tool may be appropriate. If it needs to discover sources, search is the relevant starting point.
- Does the service expose a suitable API? An API is a strong fit for structured information or functions it actually provides. It cannot fill gaps in the API’s coverage.
- Does the task need rendered content or interaction? A browser is more relevant when the task depends on a rendered page, navigation, or a user-facing workflow.
- What permissions does the tool have? A method is useful only if the agent’s application can access the needed resource and perform the needed operation.
- What does the site permit or require? Authentication, access controls, and crawler guidance can affect what a tool can retrieve. Crawler guidance is not the same as a login or security boundary.
When a task spans multiple needs, a hybrid approach may make sense—for example, using an API for structured data and a browser for a page interaction. The WebArena findings discussed above support hybrid access within that benchmark; they do not establish that a hybrid design will outperform other approaches on every real-world task.
What did the WebArena study find about API and browser agents?
The 2025 paper in the Association for Computational Linguistics Anthology reported a 38.9% success rate for its hybrid agent in its WebArena experiments. It also reported a more than 24.0% absolute improvement over web browsing alone in that comparison. The same study found API-based agents performed better than browser-only agents in its experimental setup, while hybrid agents surpassed both approaches across nearly all of its tasks.
These figures are benchmark results, not general success rates for AI agents on the open web. They describe the paper’s agents, tasks, benchmark, and experimental conditions. They should not be read as a prediction that a particular commercial agent will succeed on 38.9% of your tasks, or that adding an API will improve performance by the same amount elsewhere.
Does robots.txt block AI agents?
robots.txt is a file that gives crawling instructions to crawlers. Google Search Central explains that it tells search engine crawlers which URLs they may access. Google also cautions that robots.txt is not a way to secure a page or guarantee its removal from search results: a disallowed URL may still be discovered and indexed from links, and not every crawler is forced to comply.
Use access controls for private information. Google recommends password protection for private files; if the goal is to keep a page out of Google’s results, it recommends approaches such as noindex or removal. A crawler instruction is not authentication, and it should not be treated as a reliable security barrier.
AI-related crawlers can have different purposes
The phrase “AI crawler” can refer to systems with different roles. OpenAI’s documentation describes OAI-SearchBot as supporting visibility in ChatGPT search, GPTBot as crawling content that may be used for foundation-model training, and ChatGPT-User as handling certain user-triggered page visits. The documentation also says user-triggered visits may not be governed by robots.txt in the same way as automated crawling.
Those names and purposes describe OpenAI’s own systems; they are not a universal classification of every crawler associated with AI. A site owner should check the relevant service’s documentation and configure appropriate access controls for sensitive content rather than assume a single robots.txt rule governs every kind of request.
Quick Recap
What to remember about agent access
- An AI agent gets online information through tools its application provides; the language model does not automatically have unrestricted internet access.
- Search discovers candidate pages, fetch retrieves a known address, APIs provide structured service access, and browser tools can inspect rendered pages or interact with them.
- APIs and browsers can complement one another, but the right method depends on the task, available interfaces, permissions, and site behavior.
robots.txtgives crawler guidance. It is not a substitute for authentication or a dependable way to secure private material.
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