browser_use

BrowserUse enables agents to run browser automation tasks with natural-language instructions. It simulates human-like browsing to navigate sites, click elements, fill forms, scrape data, and execute multi-step workflows with optional live monitoring and structured results.

Usage Instructions

Use this block when your agent needs to interact with the live web (research, form submission, scraping, testing).

1

Describe the task in plain English (the task).

2

(Optional) Provide variables (secrets/values the steps can use).

3

Choose whether to save_browser_data (persist cookies/session).

4

(Optional) Select model for reasoning (defaults to gpt-4o).

5

Provide your apiKey. (You can get it from here: https://cloud.browser-use.com/)

6

Run the block → it executes asynchronously and returns a task id, success status, output, and steps taken.

Great for

• Automating repetitive web flows (login → search → click → extract).

• Collecting structured data from pages.

• Filing forms or tickets across internal tools.

• End-to-end smoke tests of web apps.

Tools

browser_use_run_task

Run a single browser automation task.

Input

Parameter	Type	Required	Description
task	string	Yes	Natural-language instruction describing what the browser should do.
variables	json	No	Key–value pairs available to the task (e.g., credentials, query terms).
save_browser_data	boolean	No	Persist session/browser data (cookies, history). Default: false.
model	string	No	LLM to use for reasoning (e.g., gpt-4o, gemini-2.0-flash). Default: gpt-4o.
apiKey	string	Yes	BrowserUse API key (must be valid and funded).

Output

Parameter	Type	Description
id	string	Execution identifier for the task (useful for logs/support).
success	boolean	Whether the task completed successfully.
output	any	Raw result (e.g., extracted data, confirmation text, structured payload).
steps	json	Detailed step list (visited URLs, DOM actions, extracted elements, timing).

Examples

Example 1 — Research summary

• Task: “Go to google.com, search ‘latest genAI eval frameworks’, open top 3 reputable results, summarize key differences.”

• Variables: { "region": "US" } (optional)

• Outcome: output contains a concise comparison; steps shows search → click → parse.

Example 2 — Form submission

• Task: “Open example.com/login, sign in with provided credentials, go to /submit, fill and submit the form, confirm the success message.”

• Variables: { "username": "user", "password": "pass" }

• Outcome: success: true and output includes confirmation; steps logs DOM actions.

Example 3 — Data extraction

• Task: “Visit site.com/pricing, extract the plan names, monthly prices, and feature lists into structured JSON.”

• Outcome: output returns structured data for downstream use.

Best Practices

• Keep instructions clear and bounded: Provide goals, constraints, and what to return (e.g., “return JSON with fields X, Y, Z”).

• Use variables for sensitive data: Pass secrets via variables to keep prompts clean.

• Persist sessions when needed: Enable save_browser_data for flows that benefit from cookies (e.g., staying logged in).

• Ask for structure: If extracting data, tell the agent the exact fields/shape to return.

• Fail fast with signal: If a selector or page changes, ensure the task returns a helpful error in output.

Troubleshooting

Symptom	Likely Cause	What to Try
success: false, empty output	Site changed layout or selector	Refine the task with clearer steps; specify buttons, forms, or URLs.
Login keeps failing	Session not persisted	Set save_browser_data: true. Pass credentials via variables.
Rate-limit or bot detection	Aggressive navigation/scraping	Slow down steps; reduce frequency; add polite delays; target fewer pages.
Unexpected model behavior	Model too weak/fast for complex flows	Set model to gpt-4o (default) or a more capable reasoning model.

Notes

• Category: tools

• Type: browser_use

• The block executes tasks asynchronously and returns once the run completes (it polls for completion under the hood).