# 🎭 Playwright MCP — AI Browser Automation (`nexgendata/playwright-mcp-server`) Actor MCP server for AI agents to control browsers via Playwright — navigate, click, type, screenshot & extract data. Give Claude or GPT web browsing abilities. 16 tools for browser automation. - **URL**: https://apify.com/nexgendata/playwright-mcp-server.md - **Developed by:** [Stephan Corbeil](https://apify.com/nexgendata) (community) - **Categories:** AI, Developer tools - **Stats:** 3 total users, 2 monthly users, 0.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $5.00 / 1,000 tool calls 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 ## Playwright MCP Server Give your AI agents a real browser. This MCP server runs Playwright on Apify's infrastructure, letting AI agents navigate websites, fill forms, click buttons, extract data, and take screenshots — all through the Model Context Protocol. ### Why Use This? - **No local browser needed** — runs on Apify's cloud with anti-blocking proxies - **16 browser tools** — navigate, click, type, screenshot, extract text/HTML, run JavaScript, and more - **Anti-blocking built in** — Apify proxy infrastructure handles CAPTCHAs and blocks - **Works with any MCP client** — Claude, OpenAI, custom agents via SSE or HTTP transport ### Available Tools (16) | Tool | Description | |------|-------------| | `navigate` | Go to a URL, wait for page load | | `screenshot` | Capture page or element as PNG | | `click` | Click elements by selector or text | | `type` | Type into input fields | | `get_text` | Extract visible text from page/element | | `get_html` | Get HTML content | | `evaluate` | Run JavaScript in page context | | `select` | Choose dropdown options | | `scroll` | Scroll page or elements | | `wait` | Wait for elements to appear/disappear | | `get_links` | Extract all links with optional filtering | | `extract_table` | Parse HTML tables to JSON | | `pdf` | Generate PDF of current page | | `fill_form` | Fill multiple form fields at once | | `get_cookies` | Read browser cookies | | `set_cookies` | Set browser cookies | ### Quick Start #### Connect via MCP (SSE) ```json { "mcpServers": { "playwright": { "url": "https://nexgendata--playwright-mcp-server.apify.actor/sse", "transport": "sse", "headers": { "Authorization": "Bearer YOUR_APIFY_API_TOKEN" } } } } ```` #### Connect via HTTP ```json { "mcpServers": { "playwright": { "url": "https://nexgendata--playwright-mcp-server.apify.actor/mcp", "transport": "http" } } } ``` ### Use Cases - **Web research agents** — Browse and extract data from any website - **Form automation** — Fill out applications, surveys, registrations - **Testing & monitoring** — Check website functionality and content - **Data extraction** — Scrape dynamic JavaScript-rendered pages - **Screenshot capture** — Visual documentation and monitoring - **Price monitoring** — Track prices across e-commerce sites ### Example: Navigate and Extract ``` Agent: "Go to example.com and get all the links" Tool calls: 1. navigate(url="https://example.com") 2. get_links() ``` ### Example: Fill a Form ``` Agent: "Search for 'web scraping' on Google" Tool calls: 1. navigate(url="https://google.com") 2. type(selector="textarea[name='q']", text="web scraping", pressEnter=true) 3. wait(selector="#search") 4. get_text(selector="#search") ``` ### Proxy Support Enable Apify proxy for anti-blocking: ```json { "proxyConfiguration": { "useApifyProxy": true } } ``` ### Pricing Pay per browser action via Apify's pay-per-event model: - **Session start**: $0.05 - **Per tool call**: $0.01 ### Support Questions? Open an issue on the actor page or contact NexGenData. # Actor input Schema ## `proxyConfiguration` (type: `object`): Apify proxy configuration for anti-blocking. ## `headless` (type: `boolean`): Run browser in headless mode. ## `viewportWidth` (type: `integer`): Browser viewport width in pixels. ## `viewportHeight` (type: `integer`): Browser viewport height in pixels. ## Actor input object example ```json { "headless": true, "viewportWidth": 1280, "viewportHeight": 720 } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("nexgendata/playwright-mcp-server").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${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 = {} # Run the Actor and wait for it to finish run = client.actor("nexgendata/playwright-mcp-server").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 '{}' | apify call nexgendata/playwright-mcp-server --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=nexgendata/playwright-mcp-server", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "🎭 Playwright MCP — AI Browser Automation", "description": "MCP server for AI agents to control browsers via Playwright — navigate, click, type, screenshot & extract data. Give Claude or GPT web browsing abilities. 16 tools for browser automation.", "version": "0.0", "x-build-id": "AdX3Xkd2bdz62TdVf" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/nexgendata~playwright-mcp-server/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-nexgendata-playwright-mcp-server", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/nexgendata~playwright-mcp-server/runs": { "post": { "operationId": "runs-sync-nexgendata-playwright-mcp-server", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/nexgendata~playwright-mcp-server/run-sync": { "post": { "operationId": "run-sync-nexgendata-playwright-mcp-server", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Apify proxy configuration for anti-blocking." }, "headless": { "title": "Headless Mode", "type": "boolean", "description": "Run browser in headless mode.", "default": true }, "viewportWidth": { "title": "Viewport Width", "type": "integer", "description": "Browser viewport width in pixels.", "default": 1280 }, "viewportHeight": { "title": "Viewport Height", "type": "integer", "description": "Browser viewport height in pixels.", "default": 720 } } }, "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 } } } } } } } } } } ```