# Stagehand Crawler (`dtrungtin/stagehand-crawler`) Actor Stagehand is a browser automation framework used to control web browsers with natural language and code. - **URL**: https://apify.com/dtrungtin/stagehand-crawler.md - **Developed by:** [Tin](https://apify.com/dtrungtin) (community) - **Categories:** AI - **Stats:** 2 total users, 2 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $20.00 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Stagehand Crawler An Apify Actor that uses [Stagehand](https://github.com/browserbasehq/stagehand) — an AI-powered browser automation framework — to execute natural language instructions on web pages. Point it at any URL, describe what you want in plain English, and the AI agent will interact with the page and return results along with a final screenshot. ### What it does 1. Visits each URL in `startUrls` 2. Runs an AI agent that follows your `instruction` using real browser interactions (clicks, typing, scrolling, navigation) 3. Captures a screenshot of the final page state and saves it to the key-value store 4. Pushes a result record to the dataset containing the outcome, a summary message, and the screenshot URL ### Input | Field | Type | Required | Description | |---|---|---|---| | `startUrls` | array | yes | URLs the crawler will visit | | `instruction` | string | yes | Natural language task for the AI agent (e.g. `"Find the price of the first product"`) | | `mode` | string | yes | Agent mode: `dom`, `hybrid`, or `cua` | | `model` | string | yes | AI model in `provider/model` format (e.g. `google/gemini-3-flash-preview`) | | `apiKey` | string | yes | API key for the selected model provider | | `proxyConfig` | object | yes | Proxy settings — Apify Proxy recommended on the platform | | `maxSteps` | integer | no | Max browser interactions before stopping (default: `20`, range: 1–20) | #### Agent modes - **`dom`** — Reads the page DOM to determine actions. Fast and cost-efficient. - **`hybrid`** — Combines DOM and visual understanding. Best for complex layouts. Requires a vision-capable model (Gemini, Claude). - **`cua`** — Computer-use agent; operates purely from screenshots. Most powerful, highest cost. #### Example input ```json { "startUrls": [{ "url": "https://www.ebay.com/" }], "instruction": "Search for 'mechanical keyboard' and return the title and price of the first result.", "mode": "hybrid", "model": "google/gemini-3-flash-preview", "apiKey": "YOUR_GOOGLE_AI_API_KEY", "maxSteps": 15, "proxyConfig": { "useApifyProxy": true } } ```` ### Output Each processed URL produces one dataset record: ```json { "url": "https://www.ebay.com/", "success": true, "message": "The first result is 'Keychron K2 Pro' priced at $89.99.", "imageUrl": "https://api.apify.com/v2/key-value-stores//records/final_screenshot_.png" } ``` The `imageUrl` links directly to the PNG screenshot saved in the default key-value store. ### Resources - [Stagehand documentation](https://docs.stagehand.dev) - [@crawlee/stagehand on npm](https://www.npmjs.com/package/@crawlee/stagehand) - [Apify SDK for JavaScript](https://docs.apify.com/sdk/js) - [Crawlee + Apify Platform guide](https://crawlee.dev/docs/guides/apify-platform) - [Apify Platform documentation](https://docs.apify.com/platform) - [Join our developer community on Discord](https://discord.com/invite/jyEM2PRvMU) # Actor input Schema ## `startUrls` (type: `array`): List of URLs where the crawler will start. ## `instruction` (type: `string`): Describe what information to extract from the page or image. ## `maxSteps` (type: `integer`): Maximum number of browser actions (clicks, typing, scrolling, etc.) the AI agent may perform before stopping. Increase for complex multi-step tasks; decrease to limit cost. ## `mode` (type: `string`): Execution mode of the agent. ## `model` (type: `string`): Model in format 'provider/model'. For hybrid mode, use Gemini or Claude models (e.g., google/gemini-3-flash-preview). ## `apiKey` (type: `string`): API key for the selected model provider. ## `proxyConfig` (type: `object`): It's required to use proxies when running on the platform. ## Actor input object example ```json { "startUrls": [ { "url": "https://images.pexels.com/photos/28337239/pexels-photo-28337239.jpeg" } ], "instruction": "Count the number of people in the image.", "maxSteps": 10, "mode": "hybrid", "model": "google/gemini-3-flash-preview", "proxyConfig": { "useApifyProxy": true } } ``` # Actor output Schema ## `overview` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "startUrls": [ { "url": "https://images.pexels.com/photos/28337239/pexels-photo-28337239.jpeg" } ], "instruction": "Count the number of people in the image.", "mode": "hybrid", "model": "google/gemini-3-flash-preview", "proxyConfig": { "useApifyProxy": true } }; // Run the Actor and wait for it to finish const run = await client.actor("dtrungtin/stagehand-crawler").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "startUrls": [{ "url": "https://images.pexels.com/photos/28337239/pexels-photo-28337239.jpeg" }], "instruction": "Count the number of people in the image.", "mode": "hybrid", "model": "google/gemini-3-flash-preview", "proxyConfig": { "useApifyProxy": True }, } # Run the Actor and wait for it to finish run = client.actor("dtrungtin/stagehand-crawler").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "startUrls": [ { "url": "https://images.pexels.com/photos/28337239/pexels-photo-28337239.jpeg" } ], "instruction": "Count the number of people in the image.", "mode": "hybrid", "model": "google/gemini-3-flash-preview", "proxyConfig": { "useApifyProxy": true } }' | apify call dtrungtin/stagehand-crawler --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=dtrungtin/stagehand-crawler", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Stagehand Crawler", "description": "Stagehand is a browser automation framework used to control web browsers with natural language and code.", "version": "0.0", "x-build-id": "t81SPlDm9suTWsIQP" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/dtrungtin~stagehand-crawler/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-dtrungtin-stagehand-crawler", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/dtrungtin~stagehand-crawler/runs": { "post": { "operationId": "runs-sync-dtrungtin-stagehand-crawler", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/dtrungtin~stagehand-crawler/run-sync": { "post": { "operationId": "run-sync-dtrungtin-stagehand-crawler", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "startUrls", "instruction", "mode", "model", "apiKey", "proxyConfig" ], "properties": { "startUrls": { "title": "Start URLs", "type": "array", "description": "List of URLs where the crawler will start.", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "instruction": { "title": "Instruction", "type": "string", "description": "Describe what information to extract from the page or image." }, "maxSteps": { "title": "Max Interaction Steps", "minimum": 1, "maximum": 20, "type": "integer", "description": "Maximum number of browser actions (clicks, typing, scrolling, etc.) the AI agent may perform before stopping. Increase for complex multi-step tasks; decrease to limit cost.", "default": 10 }, "mode": { "title": "Agent Mode", "enum": [ "dom", "hybrid", "cua" ], "type": "string", "description": "Execution mode of the agent." }, "model": { "title": "Model", "type": "string", "description": "Model in format 'provider/model'. For hybrid mode, use Gemini or Claude models (e.g., google/gemini-3-flash-preview)." }, "apiKey": { "title": "API Key", "type": "string", "description": "API key for the selected model provider." }, "proxyConfig": { "title": "Proxy configuration", "type": "object", "description": "It's required to use proxies when running on the platform." } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```