6 Best Browser Agents in 2026

TL;DR

• Context.dev best serves extraction-heavy AI applications because browser actions feed directly into clean Markdown or structured JSON.
• Browser Use best handles open-ended browsing through natural-language task execution.
• Browserbase and Stagehand best support production browser infrastructure through persistent authenticated contexts.
• Browserless best hosts existing Playwright or Puppeteer workflows through managed browser connections.
• Skyvern best handles complex forms, files, and login workflows through agent-directed browser execution.
• Playwright best supports deterministic automation through precise, code-first browser control.

What a browser agent actually is

A browser agent combines a browser runtime with software that can inspect pages and execute actions such as navigating, clicking, typing, scrolling, and extracting information. Some agents choose each action based on a goal, while others follow developer-written instructions. Search results group four distinct architectures under the same term.

• AI browser agents interpret a goal, inspect the current page, and choose the next action. Browser Use and Skyvern fit open-ended tasks across unfamiliar interfaces.
• Agent-oriented browser infrastructure provides managed browsers, persistent sessions, proxies, and observability. Browserbase lets agent frameworks or Playwright code control those browsers without requiring you to operate a browser fleet.
• Browser automation frameworks provide deterministic control through code. Playwright suits known workflows, but you own selectors, retries, deployment, and usually anti-bot handling.
• Browser-assisted web-data APIs render pages and perform browser actions to reach content, then return normalized Markdown, HTML, or structured JSON. Context.dev fits this category because extraction serves as the primary output.

Your required output should drive the choice. A completed UI task calls for an AI browser agent. A stable, predefined flow favors Playwright. Persistent authenticated interaction points toward managed browser infrastructure. Clean, current website data for an LLM pipeline favors a browser-assisted web-data API. A hybrid workflow can separate interactive browser work from repeatable data extraction.

How we evaluated these tools

We evaluated every product against the same practical criteria. These included browser actions, JavaScript rendering, authentication and session persistence, extraction quality, structured output, anti-bot handling, deployment overhead, API and MCP access, and the use case each tool serves best.

We treated browser control and data extraction as separate capabilities. A tool that clicks through an interface may return a DOM or screenshot, while a managed web-data API may normalize the page into clean Markdown or schema-shaped JSON. We also distinguished vendor-provided anti-bot features from independently verified performance.

We included pricing only when current vendor documentation confirmed it. Where public pricing could not be verified, we avoided estimates.

Context.dev

Best for

Context.dev is our top pick for AI applications that need current web data in clean Markdown or structured JSON. It works best when browser interaction serves an extraction task rather than an open-ended UI workflow.

What it is

Context.dev combines browser control with a managed scraping and crawling API. Its actions parameter supports click, type, wait, and scroll operations on JavaScript-rendered pages. Paid plans allow up to five ordered actions per request, and action requests bypass the cache.

An agent can dismiss a modal, enter a search term, scroll through loaded results, and then extract the resulting page. Context.dev can return Markdown, HTML, images, screenshots, or JSON shaped to a requested schema. The same managed stack handles rendering and related scraping infrastructure, so developers do not need to normalize inconsistent page HTML before sending the result to an LLM.

Context.dev supports MCP with OAuth, which lets compatible agents call its web-data tools directly. REST APIs and SDKs support application code and data pipelines.

Pros

• Browser actions and extraction run within one managed request, which reduces the orchestration code required between automation and parsing tools.
• Schema-shaped JSON gives AI applications predictable fields even when source websites use inconsistent HTML.
• JavaScript rendering and managed protection handling remove the need to maintain browsers, proxies, and fingerprint infrastructure for extraction workloads.
• Markdown output provides LLMs with cleaner input than a raw DOM containing navigation, scripts, and presentation markup.
• A single API covers scraping, crawling, structured extraction, and image collection.

Cons

• Context.dev has no self-hosted edition, so it will not suit developers who must run browser infrastructure inside their own environment.
• Context.dev does not target long-lived browser sessions, persistent logged-in profiles, or multi-account management. Browserbase and Stagehand fit persistent authentication better.
• Open-ended tasks that require an agent to interpret unfamiliar interfaces and choose many steps may fit Browser Use or Skyvern better.
• Deterministic workflows that need complete control over selectors, network events, and browser state may still call for Playwright.

Pricing

Context.dev uses flexible, usage-based pricing and states that pricing does not include hidden credit multipliers. Published materials do not provide enough detail for a fixed cost comparison, so developers should evaluate current pricing against their request volume, rendering needs, and extraction formats.

Browser Use

Best for

Browser Use is the strongest option here for open-ended tasks described in natural language. Its agent can inspect unfamiliar pages, choose actions, and adjust its next step based on what appears.

What it is

Browser Use offers Agents and Browser Infrastructure. Agents accept a natural-language task and return the completed result. Browser Infrastructure launches a managed cloud browser that your Playwright or Puppeteer code controls through CDP.

An open-source local library provides another path when you want to run the agent within your own environment. You then take responsibility for browser deployment and related infrastructure.

Pros

Browser Use supports both autonomous task execution and direct browser control. You can begin with natural-language agents, then use Playwright or Puppeteer when a workflow needs explicit logic. The open-source library also gives you a local option without requiring the hosted service.

Cons

Browser Use targets general browser interaction rather than managed data normalization. If your main output is clean Markdown or schema-shaped JSON, you may need to add extraction and normalization steps. Agent-planned actions also provide less deterministic behavior than a fixed Playwright script, which can complicate testing for stable workflows.

Pricing

Current pricing was not verifiable from the supplied first-party documentation. Check Browser Use’s pricing page before estimating production costs, especially for workloads that combine agent execution with hosted browser sessions.

Browserbase and Stagehand

Best for

Browserbase and Stagehand are the strongest pick for production cloud-browser infrastructure, especially when your application needs persistent authenticated sessions.

What it is

Browserbase runs managed cloud browsers, while Stagehand provides an SDK that combines familiar automation APIs with agent-oriented actions. You can use deterministic browser commands for known steps and agent actions when the interface requires interpretation.

Browserbase Contexts preserve cookies, authentication tokens, localStorage, IndexedDB, session storage, service workers, form data, and browser preferences across sessions. A Context remains available until you delete it. However, individual websites can still expire or revoke authentication.

Pros

• Contexts support logged-in workflows that span multiple browser sessions.
• Stagehand lets you mix direct automation with agent-driven interaction.
• Managed browsers reduce the infrastructure required to run production browser fleets.
• Session persistence suits applications that revisit authenticated websites over time.

Cons

• Browserbase focuses on browser infrastructure rather than normalized, LLM-ready extraction. You may need separate parsing and schema validation.
• Persistent Contexts cannot prevent a website from expiring tokens or requesting authentication again.
• Extraction-heavy pipelines may require more engineering than a managed web-data API.

Pricing

The supplied first-party documentation does not confirm current pricing. Check Browserbase’s current plans and usage terms before estimating production costs.

Browserless

Best for

Browserless best serves developers who already run Puppeteer or Playwright workflows and want managed browser infrastructure without rewriting their automation code.

What it is

Browserless provides browser as a service through WebSocket connections. Existing Puppeteer and Playwright code can connect to its hosted browsers instead of launching and maintaining local browser instances. Browserless supports multiple browser engines and regional endpoints for running sessions closer to users or target sites.

BrowserQL adds a declarative query layer for browser tasks. Browserless also provides REST APIs for jobs such as screenshots, PDFs, and page scraping.

Pros

• Browserless preserves the core logic in existing Puppeteer and Playwright workflows.
• Stealth mode provides anti-detection features without requiring you to manage browser fingerprints and related infrastructure.
• Live human handoff lets a person enter an active session when automation requires review or manual input.
• Regional endpoints and multiple browser engines give you more control over where and how workflows run.

Cons

• Browserless supplies browser infrastructure rather than an autonomous AI agent that plans open-ended tasks.
• Browserless does not automatically turn every page into normalized, LLM-ready structured data. You may still need extraction, schema validation, and cleanup code.
• Stealth mode does not guarantee access to every protected site, and published feature support should not be treated as an independently verified success rate.

Pricing

The first-party documentation reviewed for this comparison does not confirm current prices. Check Browserless directly for current plan limits and usage charges.

Skyvern

Best for

Skyvern fits complex, multi-step workflows on unfamiliar sites, especially tasks involving authentication, forms, file operations, branching steps, or CAPTCHAs.

What it is

Skyvern combines LLM reasoning, screenshots, computer vision, DOM extraction, and Playwright execution. The agent interprets each page and chooses actions without relying entirely on predefined selectors. It can also return extracted data that follows a supplied JSON Schema.

Pros

• Skyvern supports stored credentials, 2FA workflows, CAPTCHA handling, and proxy configuration.
• Browser sessions can run for up to six hours, while reusable profiles preserve state for later workflows.
• API and MCP access let AI applications start workflows and consume results programmatically.
• A self-hosted edition gives you more control over deployment and data handling.
• JSON Schema support makes workflow results easier to validate before an LLM or downstream service consumes them.

Cons

• Complex agent decisions can be less deterministic than explicit Playwright scripts.
• Self-hosting transfers deployment, monitoring, scaling, and browser maintenance to your engineering team.
• Skyvern targets workflow completion rather than managed normalization of large volumes of web content. Context.dev fits better when clean Markdown or structured JSON extraction is the primary output.
• CAPTCHA support does not establish a universal success rate across websites and challenge types.

Pricing

The reviewed first-party documentation does not confirm current pricing. Check Skyvern’s current plans and self-hosting costs before comparing total deployment expense.

Playwright

Best for: Playwright fits known, repeatable workflows where deterministic browser control matters more than autonomous decision-making.

What it is: Playwright is an open-source browser automation framework rather than an autonomous AI browser agent. Developers write explicit code for navigation, interaction, and extraction across Chromium, Firefox, and WebKit.

Pros:

• Playwright gives you precise control over page actions, JavaScript execution, network requests, and browser contexts.
• Playwright can save and reuse authentication state, including cookies and browser storage. Reusable storage state supports logged-in workflows without repeating authentication for every run.
• Explicit scripts make behavior easier to test and debug when pages and expected actions remain predictable.

Cons:

• You must create and maintain selectors, navigation logic, and extraction code. Website changes can break those assumptions.
• Your application must manage retries and browser infrastructure unless you pair Playwright with a hosted browser provider.
• Playwright does not provide managed anti-bot handling or autonomous task planning. You must add those capabilities separately.
• Raw page content still requires parsing and normalization before an LLM can consume consistent structured data.

Pricing: Playwright is open source and has no license cost. You still pay for compute, proxies, monitoring, and the engineering work required to operate browser automation in production.

Comparison table

Product	Best for	Browser actions	JS rendering	Auth/session persistence	Structured output	Anti-bot handling	Deployment model	API/MCP access
Context.dev	LLM-ready web data	Yes, up to 5 on paid plans	Yes	No persistent sessions	Markdown and schema JSON	Managed	Hosted	REST, SDK, MCP
Browser Use	Open-ended agentic browsing	Autonomous or CDP	Yes	Cloud browser sessions	Partial	Not specified	Cloud or local	API
Browserbase and Stagehand	Persistent authenticated workflows	Yes, via Stagehand	Yes	Persistent Contexts	SDK extraction	Managed browsers	Hosted	API and SDK
Browserless	Hosting existing Playwright or Puppeteer code	Yes	Yes	Persistent sessions	Partial	Stealth mode	Hosted	REST, WebSocket
Skyvern	Complex forms, files, and login flows	Autonomous	Yes	Profiles and sessions	JSON Schema	CAPTCHA and proxy support	Cloud or self-hosted	API, MCP
Playwright	Deterministic code-first automation	Yes, coded	Yes	Storage state	Developer-built	Developer-managed	Self-managed	Library

Browser agents vs. managed web-data APIs

Browser agents optimize for completing interactions inside a browser. An agent inspects a page, chooses an action, observes the result, and repeats until it finishes the task. Browser access may expose the DOM, screenshots, or an extraction command, but developers often still need to remove navigation, resolve inconsistent HTML, validate fields, and shape the result for an LLM.

Managed web-data APIs optimize for returning usable website content. These services handle browser rendering and extraction behind an API, then normalize the retrieved content into formats such as Markdown or schema-shaped JSON. Context.dev fits this category because browser control supports the extraction job rather than serving as a persistent environment for open-ended automation.

DOM access alone does not provide consistent structured data. Two sites can display the same company details while using different elements, labels, and JavaScript loading patterns. A general-purpose browser agent can find those details, but your application may still need site-specific parsing and output validation. A managed web-data API takes responsibility for more of that normalization layer.

Choose based on the final output. Use a general-purpose agent when you need to navigate unfamiliar interfaces, maintain authenticated sessions, or complete multi-step UI tasks. Use a managed web-data API when you need clean, current content for retrieval, enrichment, or an LLM pipeline. A hybrid workflow fits applications that require both interaction and repeatable structured extraction.

A hybrid architecture example

A hybrid architecture works well when an agent must complete an interactive task before an LLM can use the resulting web data. For example, Browser Use or Skyvern can log into a distributor portal, navigate unfamiliar controls, apply inventory filters, and collect the resulting product URLs.

The agent can then pass those URLs to Context.dev through REST or MCP. Context.dev renders each page, uses browser actions to reveal hidden content when needed, and returns schema-shaped JSON for the LLM. The agent owns the stateful interaction, while Context.dev owns repeatable extraction and output normalization.

Protected data requires a different boundary. If product details remain available only inside the authenticated session, keep extraction in the agent or use persistent browser infrastructure such as Browserbase. Context.dev fits when the handoff produces accessible URLs that need clean, current data.

Splitting responsibilities reduces agent prompts and removes the need to build a normalization layer around raw DOM output. One universal browser tool often adds maintenance when separate interaction and extraction components fit the workflow better.

Decision framework

Start with the output you need, then choose the tool that owns the fewest unnecessary responsibilities.

• If you need a completed UI task and the steps may change, choose an AI browser agent such as Browser Use.
• If you need persistent authenticated sessions and managed cloud browsers, choose Browserbase with Stagehand.
• If you know every step and need deterministic control, choose Playwright. You will own selectors, retries, deployment, and anti-bot handling.
• If your existing Playwright or Puppeteer code needs managed browser infrastructure, choose Browserless.
• If your workflow involves unfamiliar forms, authentication, files, or other multi-step interactions, choose Skyvern.
• If you need clean, current, structured web data for an LLM or application, choose Context.dev. Its managed extraction layer handles browser-assisted access and returns usable output without requiring you to normalize page content yourself.

Split the workflow when interaction and extraction require different strengths. Browser Use or Skyvern can complete an authenticated task, while Context.dev can extract structured data from the resulting public pages or URLs. A hybrid keeps open-ended browser control separate from repeatable data delivery.

FAQs

What is a browser agent compared with a browser automation framework?

A browser agent chooses actions based on a goal and the current page. A framework such as Playwright executes developer-defined actions, selectors, and recovery logic. Agents suit unfamiliar interfaces, while frameworks suit stable workflows that require deterministic control.

Can Context.dev replace Playwright or Browserbase?

Context.dev can replace them when you need JavaScript rendering, limited browser actions, and clean extracted data. Playwright offers deeper code-level control, while Browserbase supports persistent authenticated browser contexts. Context.dev does not target long-lived sessions or general-purpose UI automation.

Do browser agents handle CAPTCHAs and anti-bot protection?

Support varies by product. Skyvern documents CAPTCHA handling, proxies, and credential workflows. Context.dev manages anti-bot infrastructure for extraction use cases, while Playwright leaves protection handling to you. Vendor documentation does not provide independently verified success rates across sites or challenge types.

When should I use MCP instead of a REST API?

Use MCP when an AI client needs to discover and call web-data tools during its reasoning loop. Use REST when application code controls each request and requires predictable request handling. Context.dev and Skyvern support MCP, while REST remains a straightforward choice for backend pipelines.

Can I combine a browser agent with a web-data API?

Yes. Browser Use or Skyvern can complete an authenticated workflow, then pass discovered public URLs to Context.dev for normalized Markdown or schema-shaped JSON. Keep private-page extraction inside the authenticated browser unless the web-data API explicitly supports transferring the required session state.

Do these tools support authenticated or logged-in sessions?

Support differs in depth. Browserbase Contexts preserve cookies, tokens, browser storage, and preferences across sessions. Browserless, Skyvern, and Playwright also support reusable session state. Context.dev focuses on extraction rather than persistent logged-in browsing.

Choosing the right browser agent for your stack

Choose a browser agent based on the output your application needs. General-purpose agents suit open-ended UI tasks, persistent authenticated sessions, and complex workflows. Deterministic automation frameworks fit known interaction sequences. A managed web-data API fits pipelines that need current website content in a consistent structure.

Context.dev should be the default when your LLM needs clean, structured web data without a separate scraping stack. Its actions parameter can interact with dynamic pages before the managed API returns usable output. For workflows that also require long-lived sessions or open-ended decisions, pair Context.dev with a general-purpose browser agent rather than forcing either tool to handle both roles. Start by testing actions against one extraction-heavy workflow and compare the returned data with the normalization code you maintain today.