Provides web automation capabilities through Playwright running on Cloudflare's infrastructure, enabling browser control for navigation, interaction, and screenshot capture
Deploys and runs as a Cloudflare Workers application, providing serverless browser automation through Playwright for web scraping and testing tasks
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Cloudflare Playwright MCP go to github.com and take a screenshot of the trending page"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
This project demonstrates how to use Playwright with Cloudflare Workers as a Model Control Protocol (MCP) server using Cloudflare Playwright MCP.
It enables AI assistants to control a browser through a set of tools, allowing them to perform web automation tasks like navigation, typing, clicking, and taking screenshots.
The server can be used with various AI platforms including Cloudflare AI Playground, Claude Desktop, and GitHub Copilot in VS Code.
Follow these steps to set up and deploy the project:
Install dependencies:
npm ciDeploy to Cloudflare Workers:
npx wrangler deploy
Cloudflare playground AI is a great way to test MCP servers using LLM models available in Workers AI.
Navigate to https://playground.ai.cloudflare.com/
Ensure model is set to llama-3.3-70b-instruct-fp8-fast
In MCP Servers, set URL to https://[my-mcp-url].workers.dev/sse
Click Connect
Status should update to Connected and it should list 14 available tools
You can now start to interact with the model, and it will run necessary tools to accomplish what was requested.
For best results, give simple instructions consisting of one single action, e. g., "Create a new todo entry", "Go to cloudflare site", "Take a screenshot"
Example of a conversation:
Role | Message |
User | Go to demo.playwright.dev/todomvc |
Assistant | runs browser_navigate tool The page has been navigated to https://demo.playwright.dev/todomvc/. The page title is "React • TodoMVC". The page snapshot shows the content of the page, including a heading, a textbox, and several links. |
User | Create some todo entry |
Assistant | runs browser_type tool A new todo entry "Buy groceries" has been created. The page snapshot shows the updated content of the page, including the new todo entry. |
User | Nice. Now create a todo in parrot style |
Assistant | runs browser_type tool A new todo entry "Polly wants a cracker" has been created in parrot style. The page snapshot shows the updated content of the page, including the new todo entry. |
User | And create another todo in yoda style |
Assistant | runs browser_type tool A new todo entry "A walk, I must take" has been created in Yoda style. The page snapshot shows the updated content of the page, including the new todo entry. |
User | Take a screenshot |
Assistant | runs browser_take_screenshot tool |
User | Now click the checkbox of the parrot todo entry |
Assistant | runs browser_clickt tool The checkbox of the parrot todo entry "Polly wants a cracker" has been clicked. The page snapshot shows the updated content of the page, with the checkbox now checked. |
User | Take a screenshot |
Assistant | runs browser_take_screenshot tool |
User | Remove completed todo entries |
Assistant | runs browser_clickt tool The "Clear completed" button has been clicked. The page snapshot shows the updated content of the page, with the completed todo entry "Polly wants a cracker" removed. |
User | Take a final screenshot |
Assistant | runs browser_take_screenshot tool |
As of now, Claude Desktop only supports local MCP servers. To use playground-mcp with Claude Desktop we make use of mcp-remote, a tool that proxies remote MCP servers and exposes them locally. Use the following configuration:
Open the configuration file for Claude Desktop.
Add the following JSON snippet under the mcpServers section:
A screenshot of the current page has been taken. The screenshot is in PNG format and is 56KB in size.
A screenshot of the current page has been taken. The screenshot is in PNG format and is 58KB in size.
A final screenshot of the current page has been taken. The screenshot is in PNG format and is 50KB in size.{
"mcpServers": {
"cloudflare-playwright-mcp": {
"command": "npx",
"args": [
"mcp-remote",
"https://[my-mcp-url].workers.dev/sse"
]
}
}
}Save the configuration file and restart Claude Desktop to apply the changes.
This setup ensures that Claude Desktop can communicate with the Cloudflare Playwright MCP server.
Here's an example of a session opening the TODO demo app, adding "buy lemons" and doing a screenshot, taking advantage of playwright-mcp tools and Browser Rendering:
You can install the Playwright MCP server using the VS Code CLI:
# For VS Code
code --add-mcp '{"name":"cloudflare-playwright","type":"sse","url":"https://[my-mcp-url].workers.dev/sse"}'# For VS Code Insiders
code-insiders --add-mcp '{"name":"cloudflare-playwright","type":"sse","url":"https://[my-mcp-url].workers.dev/sse"}'After installation, the Playwright MCP server will be available for use with your GitHub Copilot agent in VS Code.
Execute custom Playwright JS code against the current page
| Name | Required | Description | Default |
|---|---|---|---|
| code | Yes | The Playwright code to execute. Must be an async function declaration that takes a page parameter. Example: async function run(page) { console.log(await page.title()); return await page.title(); } Returns an object with: - result: The return value from your function - logs: Array of console logs from execution - errors: Array of any errors encountered Example response: {"result": "Google", "logs": ["[log] Google"], "errors": []} |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden and does well by disclosing key behavioral traits: it executes code asynchronously, requires a specific function structure (async with page parameter), and details the return format (result, logs, errors). It doesn't mention rate limits, auth needs, or destructive effects, but covers execution mechanics adequately for a tool with no annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that directly states the tool's purpose with zero waste. Every word earns its place by specifying the action, code type, and target, making it highly efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given one parameter with full schema coverage and no output schema, the description is reasonably complete. It explains the execution process and return format, compensating for the lack of output schema. However, it doesn't address potential errors or side effects beyond the listed response fields, leaving minor gaps for a code execution tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description adds value by emphasizing the code must be 'Playwright JS' and executed 'against the current page', providing context beyond the schema's technical details. It doesn't elaborate on parameter syntax beyond the example, but enhances understanding of the tool's scope.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('execute') and resource ('custom Playwright JS code') with the target ('against the current page'). It distinguishes from siblings like get-context or get-screenshot by focusing on code execution rather than retrieval or capture. However, it doesn't explicitly differentiate from init-browser in terms of browser lifecycle management.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for executing custom code on a page, suggesting it's for dynamic interactions beyond simple data fetching. No explicit guidance on when to use vs. alternatives like get-full-dom for static content or prerequisites (e.g., requires an initialized browser). The context is clear but lacks specific exclusions or named alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get the full DOM of the current page. (Deprecated, use get-context instead)
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool's purpose and deprecation status but lacks details about what 'full DOM' includes (e.g., structure, limitations), performance implications, or error handling. The description adds some context (deprecation) but doesn't fully compensate for the missing annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with just two sentences that each serve a distinct purpose: the first states the tool's function, and the second provides critical usage guidance. There is zero wasted text, and the information is front-loaded with the core purpose immediately clear.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 0 parameters, no annotations, and no output schema, the description provides adequate context for a simple, deprecated tool. It clearly explains what the tool does and why it shouldn't be used, which is sufficient for its complexity level. However, it could be more complete by explaining what 'full DOM' entails or linking to documentation for the replacement tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, focusing instead on the tool's purpose and usage guidance. This meets the baseline expectation for tools without parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Get the full DOM') and the target resource ('of the current page'), providing a complete verb+resource combination. It also explicitly distinguishes from its sibling 'get-context' by marking itself as deprecated and recommending the alternative, which enhances clarity about its role relative to other tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when not to use this tool ('Deprecated, use get-context instead'), directly naming the alternative sibling tool. This gives clear, actionable advice for tool selection, helping the agent avoid deprecated functionality in favor of the recommended option.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get a complete snapshot of the page including all visible content (text, images, forms, etc.) for understanding the full context
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the tool captures 'all visible content' but doesn't specify details like whether it requires an active browser session, how it handles dynamic content, potential performance impacts, or what the output format looks like. This leaves significant gaps for a tool that likely interacts with web pages.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that efficiently conveys the core purpose without redundancy. It's front-loaded with the main action and resource, making it easy to parse. However, it could be slightly more concise by avoiding the parenthetical elaboration, which adds minor verbosity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's likely complexity in capturing web page snapshots, the description is insufficient. With no annotations, no output schema, and minimal behavioral details, it fails to provide enough context for effective use. It doesn't explain what 'complete snapshot' entails, how it differs from siblings, or what the agent should expect as a result, leaving critical gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters, and the schema description coverage is 100%, so there are no parameters to document. The description appropriately doesn't add unnecessary parameter details, aligning with the empty input schema. A baseline score of 4 is applied as it doesn't need to compensate for any parameter gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with specific verbs ('Get a complete snapshot') and resources ('page including all visible content'), making it easy to understand what it does. However, it doesn't explicitly differentiate from sibling tools like 'get-full-dom' or 'get-text-snapshot', which likely serve similar but distinct purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides minimal guidance on when to use this tool, only mentioning it's 'for understanding the full context'. It doesn't specify when to choose this over alternatives like 'get-text-snapshot' or 'get-screenshot', nor does it mention any prerequisites or exclusions, leaving usage unclear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get a snapshot focused on interactive elements (buttons, links, inputs) with annotated screenshot for UI automation
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It describes what the tool does (gets a snapshot with annotations) but lacks details on behavioral traits such as performance characteristics, error handling, or whether it requires specific browser states. This is a significant gap for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that efficiently conveys the tool's purpose and context without any wasted words. It is front-loaded with key information ('Get a snapshot focused on interactive elements') and appropriately sized for its complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no parameters, no annotations, and no output schema, the description is minimally adequate. It explains what the tool does and its intended use ('for UI automation'), but it lacks details on output format, behavioral constraints, or how it differs from siblings. This leaves gaps in understanding for effective agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't mention any parameters, which is appropriate. A baseline score of 4 is applied since there are no parameters to document, and the description doesn't add unnecessary details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get a snapshot focused on interactive elements (buttons, links, inputs) with annotated screenshot for UI automation.' It specifies the verb ('Get'), resource ('snapshot'), and scope ('interactive elements'), though it doesn't explicitly differentiate from sibling tools like 'get-full-snapshot' or 'get-screenshot' beyond mentioning 'focused on interactive elements.'
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context ('for UI automation') and suggests when to use it (when needing interactive elements), but it doesn't provide explicit guidance on when to choose this tool over alternatives like 'get-full-snapshot' or 'get-screenshot.' No exclusions or prerequisites are mentioned, leaving usage somewhat open to interpretation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get a screenshot of the current page
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states what the tool does but lacks details on traits like whether it requires a browser session to be active, if it captures the entire viewport or a specific area, potential delays or failures, or the format of the output (e.g., image data, file path). This is a significant gap for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with zero waste—it directly states the tool's function without unnecessary words. It is appropriately sized and front-loaded, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (capturing a screenshot likely involves browser state and output handling), lack of annotations, and no output schema, the description is incomplete. It doesn't address behavioral aspects like dependencies on an active page or what the output contains, leaving the agent with insufficient context for reliable use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add param info, which is appropriate here. Baseline is 4 for 0 params, as the description doesn't need to compensate for any schema gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get') and resource ('screenshot of the current page'), making the tool's purpose immediately understandable. It doesn't explicitly differentiate from siblings like 'get-full-dom' or 'get-context', but the specificity of 'screenshot' provides inherent distinction. This is not a tautology of the name and is appropriately specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'get-full-dom' (which might provide DOM structure) or 'get-context' (which might provide textual context). It implies usage when a visual capture is needed, but lacks explicit context, prerequisites, or exclusions, leaving the agent to infer based on tool names alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get all text content from the page (headings, paragraphs, lists) for reading and content extraction
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool 'gets all text content' but does not specify behavioral traits such as performance characteristics (e.g., speed, pagination), error handling, or whether it requires specific page states (e.g., loaded page). This leaves gaps in understanding how the tool behaves beyond its basic function.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core action ('Get all text content') and specifies the scope ('from the page') and use cases ('for reading and content extraction'). Every word contributes to understanding without waste, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (simple text extraction with no parameters) and lack of annotations or output schema, the description is minimally complete. It states what the tool does but lacks details on output format (e.g., structured text, raw string) or behavioral context, which could be important for an agent to use it effectively in varied scenarios.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately does not discuss parameters, focusing on the tool's purpose instead. This meets the baseline for tools with no parameters, as it avoids unnecessary details and adds value by clarifying the tool's intent.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with specific verbs ('get all text content') and resources ('from the page'), specifying content types like headings, paragraphs, and lists. It distinguishes the tool by focusing on text extraction for reading, but does not explicitly differentiate it from sibling tools like get-full-dom or get-full-snapshot, which might also retrieve text content.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for 'reading and content extraction,' suggesting when to use this tool (e.g., for text analysis). However, it lacks explicit guidance on when not to use it or alternatives among sibling tools (e.g., vs. get-full-dom for full DOM or get-screenshot for visual capture), leaving usage context partially inferred.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Initialize a browser with a URL
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | The URL to navigate to |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action ('Initialize a browser') but doesn't explain what this entails—whether it launches a new browser instance, reuses an existing one, requires specific permissions, has side effects like opening windows, or what happens on failure. This leaves significant gaps in understanding the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It's front-loaded with the core action and resource, making it easy to parse quickly. Every word earns its place by conveying essential information without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of initializing a browser (which could involve launching processes, handling errors, or managing sessions) and the lack of annotations and output schema, the description is incomplete. It doesn't address what the tool returns, potential errors, or behavioral nuances, leaving the agent with insufficient context for reliable use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, with the 'url' parameter fully documented in the schema as 'The URL to navigate to'. The description adds no additional meaning beyond this, such as URL format examples or constraints. Since the schema does the heavy lifting, the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Initialize a browser') and the target resource ('with a URL'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'get-screenshot' or 'get-full-dom' which might also involve browser operations, so it doesn't fully distinguish itself from alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'get-screenshot' or 'get-full-dom'. It doesn't mention prerequisites (e.g., needing a browser session first) or exclusions, leaving the agent to infer usage context from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
v1.0.0get-contextget-full-dom1 field changedInput schema / additionalPropertiesRemoved value: -falseget-full-snapshotget-interactive-snapshotget-screenshot1 field changedInput schema / additionalPropertiesRemoved value: -falseget-text-snapshotexecute-codeget-contextget-full-domget-screenshotinit-browserScored across 7 tools
Most tools have distinct purposes, with clear separation between code execution, DOM/snapshot retrieval, and browser initialization. However, get-full-dom and get-context (implied by deprecation note) could cause confusion, and the various snapshot tools (full, interactive, text) might overlap slightly in content extraction scenarios.
All tool names follow a consistent verb-object pattern with hyphen separation (e.g., execute-code, get-screenshot, init-browser). The naming is predictable and readable throughout the set, with no mixing of conventions.
With 7 tools, this server is well-scoped for Playwright automation, covering core operations like browser setup, code execution, and various snapshot types. Each tool serves a clear purpose without bloat, making it manageable and functional.
The toolset covers essential Playwright workflows: initialization, code execution, and multiple snapshot types for different contexts. A minor gap exists in navigation or page interaction tools (e.g., click, type), but agents can work around this using execute-code for custom actions.
AI-powered browser automation — navigate, click, fill forms, and extract data from any website.
AI-powered web automation. Navigate websites using AI agents for one page or a thousand
AI-powered web automation. Navigate websites using AI agents for one page or a thousand
Web search, browser automation, scraping, crawling and CAPTCHA solving for AI agents.
