{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"npm-executeautomation-playwright-mcp-server","slug":"executeautomation-playwright-mcp-server","name":"@executeautomation/playwright-mcp-server","type":"mcp","url":"https://executeautomation.github.io/mcp-playwright/","page_url":"https://unfragile.ai/executeautomation-playwright-mcp-server","categories":["mcp-servers"],"tags":["playwright","automation","AI","Claude MCP"],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"npm-executeautomation-playwright-mcp-server__cap_0","uri":"capability://automation.workflow.browser.automation.via.mcp.protocol","name":"browser-automation-via-mcp-protocol","description":"Exposes Playwright browser automation capabilities through the Model Context Protocol, allowing Claude and other MCP-compatible clients to control headless and headed browsers (Chromium, Firefox, WebKit) by translating natural language instructions into Playwright API calls. The server acts as a bridge between LLM reasoning and browser control, handling session management, context switching, and command serialization across the MCP transport layer.","intents":["I want Claude to automate web scraping tasks by controlling a browser directly","I need to enable AI agents to interact with web applications that require JavaScript execution","I want to build an AI-powered RPA solution that can navigate complex web workflows","I need Claude to test web applications by simulating user interactions"],"best_for":["AI engineers building autonomous web automation agents","Teams integrating Claude with Playwright for end-to-end testing","Developers creating no-code/low-code RPA solutions powered by LLMs","QA automation teams augmenting test suites with AI-driven interaction"],"limitations":["No built-in retry logic for flaky network conditions — requires client-side implementation","Single browser instance per MCP server connection — concurrent automation requires multiple server instances","Playwright's inherent limitations apply: no support for Flash, Java applets, or legacy ActiveX controls","MCP protocol overhead adds ~50-200ms latency per command compared to direct Playwright SDK usage","No native support for proxy rotation or IP spoofing — must be configured at OS/network level"],"requires":["Node.js 16+","Playwright 1.40+ (browser binaries: Chromium, Firefox, or WebKit)","MCP-compatible client (Claude Desktop, Cline, or custom MCP host)","System with sufficient memory for browser instances (minimum 512MB per browser)"],"input_types":["natural language instructions from LLM","structured MCP tool calls with parameters","URLs and selectors as strings","JavaScript code snippets for page evaluation"],"output_types":["structured JSON responses with page state","screenshot data (base64 or file paths)","extracted DOM content and text","boolean success/failure indicators with error messages"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm-executeautomation-playwright-mcp-server__cap_1","uri":"capability://automation.workflow.page.navigation.and.url.control","name":"page-navigation-and-url-control","description":"Provides MCP tools to navigate to URLs, handle page loads, manage browser history (back/forward), and wait for navigation events. The implementation wraps Playwright's navigation APIs (page.goto, page.goBack, page.goForward) with timeout handling, load state detection, and error propagation back to the LLM client, enabling reliable multi-step web workflows.","intents":["I want Claude to navigate through a multi-step web form or checkout flow","I need the AI to handle page redirects and wait for dynamic content loading","I want to automate login flows that involve multiple page transitions","I need the agent to gracefully handle navigation timeouts and retry"],"best_for":["Web scraping workflows requiring sequential page navigation","E-commerce automation (product browsing, checkout flows)","Multi-page form filling and submission","Authentication and session-based workflows"],"limitations":["No built-in handling for popup windows or new browser contexts — requires explicit context management","Timeout values are fixed or require reconfiguration; no dynamic timeout adjustment based on page complexity","Navigation waits only for 'load' or 'networkidle' states — doesn't detect custom JavaScript-based readiness signals","Cannot distinguish between intentional redirects and error pages without additional DOM inspection"],"requires":["Active Playwright browser instance","Valid URL format (http/https)","Network connectivity to target domain","MCP client capable of handling async navigation responses"],"input_types":["URL string (http/https)","navigation direction ('back', 'forward')","wait condition ('load', 'networkidle', 'domcontentloaded')","timeout value in milliseconds"],"output_types":["navigation success/failure status","final URL after redirects","page title and metadata","error messages with HTTP status codes"],"categories":["automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm-executeautomation-playwright-mcp-server__cap_10","uri":"capability://tool.use.integration.mcp.protocol.transport.and.serialization","name":"mcp-protocol-transport-and-serialization","description":"Implements the Model Context Protocol transport layer, handling JSON-RPC message serialization, tool registration, request/response routing, and client communication. Manages the MCP server lifecycle, tool discovery, and protocol compliance, enabling seamless integration with MCP-compatible clients (Claude Desktop, Cline, custom hosts) without requiring application-level protocol handling.","intents":["I want to integrate Playwright automation into Claude Desktop or Cline without custom code","I need to expose Playwright tools to any MCP-compatible client","I want to ensure protocol compliance and reliable message delivery","I need to manage tool discovery and capability advertisement"],"best_for":["Teams integrating Playwright with Claude or other LLM clients via MCP","Developers building custom MCP hosts that need Playwright support","Organizations standardizing on MCP for AI tool integration","Automation platforms requiring protocol-agnostic tool exposure"],"limitations":["MCP protocol overhead adds ~50-200ms latency per tool call compared to direct SDK usage","Tool discovery is static; no dynamic tool registration or capability negotiation","Message size limits may apply depending on MCP client implementation; large responses may be truncated","No built-in authentication or authorization; security relies on client-side access control","Protocol version compatibility issues if client and server use different MCP versions"],"requires":["Node.js 16+ with MCP SDK","MCP-compatible client (Claude Desktop 0.1+, Cline, or custom host)","Network connectivity between client and server (local or remote)"],"input_types":["MCP tool call requests (JSON-RPC format)","tool parameters as JSON"],"output_types":["MCP tool response (JSON-RPC format)","tool results as JSON","error responses with error codes"],"categories":["tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm-executeautomation-playwright-mcp-server__cap_2","uri":"capability://automation.workflow.dom.element.selection.and.querying","name":"dom-element-selection-and-querying","description":"Enables CSS selector and XPath-based element discovery on the current page, returning element metadata (text content, attributes, bounding box, visibility state) without interaction. Uses Playwright's locator API under the hood with support for complex selectors, shadow DOM traversal, and element filtering by visibility/enabled state, allowing LLMs to inspect page structure before taking action.","intents":["I want Claude to find a specific button or form field by its label or text content","I need the AI to verify that an element exists and is visible before clicking it","I want to extract all links from a page matching a pattern","I need the agent to locate elements within shadow DOM or iframes"],"best_for":["Web scraping with complex DOM structures","Intelligent form filling that requires element discovery before interaction","Accessibility-aware automation (finding elements by ARIA labels)","Dynamic page analysis where element selectors change between page loads"],"limitations":["Shadow DOM and iframe traversal requires explicit context switching — no automatic cross-boundary querying","XPath queries are slower than CSS selectors; no query optimization or caching","Element metadata (bounding box, visibility) is computed at query time and may be stale if page updates","No support for pseudo-element matching (::before, ::after content)","Large result sets (1000+ elements) may cause performance degradation without pagination"],"requires":["Active Playwright page instance","Valid CSS selector or XPath expression","Target page must be loaded and DOM accessible","For iframe queries: explicit iframe context or nested selector syntax"],"input_types":["CSS selector string","XPath expression","element filter criteria (visible, enabled, checked)","text content pattern (substring or regex)"],"output_types":["array of element objects with text, attributes, bounding box","element count","visibility and enabled state flags","error if selector matches no elements"],"categories":["automation-workflow","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm-executeautomation-playwright-mcp-server__cap_3","uri":"capability://automation.workflow.user.interaction.simulation","name":"user-interaction-simulation","description":"Simulates user interactions (click, type, select, check/uncheck, drag-and-drop, keyboard shortcuts) on page elements using Playwright's action APIs. Handles element waiting, focus management, and input validation, translating high-level interaction intents from the LLM into low-level browser events with proper event sequencing and timing.","intents":["I want Claude to fill out a form by typing into text fields and selecting dropdown options","I need the AI to click buttons and links in the correct sequence","I want to automate keyboard shortcuts (Ctrl+A, Enter, Tab navigation)","I need the agent to handle drag-and-drop interactions on complex UI elements"],"best_for":["Form automation and data entry workflows","E-commerce checkout and purchase flows","Web application testing with user interaction simulation","Accessibility testing (keyboard navigation, focus management)"],"limitations":["No native support for file uploads via <input type='file'> — requires workaround with setInputFiles()","Drag-and-drop on custom JavaScript-based drag handlers may fail if handlers don't respond to Playwright's synthetic events","Keyboard input timing is fixed; no support for variable typing speed or human-like input delays","Click coordinates are calculated at action time; if page layout shifts, clicks may miss target","No built-in double-click or triple-click support — requires manual event sequencing"],"requires":["Active Playwright page instance with loaded DOM","Valid element selector or locator","Element must be visible and in viewport (or scrollable into view)","For keyboard actions: target element must be focusable"],"input_types":["element selector (CSS or XPath)","action type (click, type, select, check, drag)","text input for typing actions","keyboard key names (Enter, Tab, Escape, etc.)","coordinates for drag-and-drop"],"output_types":["action success/failure status","error messages (element not found, not clickable, etc.)","updated page state after interaction","validation errors from form fields"],"categories":["automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm-executeautomation-playwright-mcp-server__cap_4","uri":"capability://data.processing.analysis.page.content.extraction.and.analysis","name":"page-content-extraction-and-analysis","description":"Extracts and analyzes page content including text, HTML, structured data, and page metadata. Supports full-page text extraction, HTML snapshot capture, JSON-LD/microdata parsing, and custom JavaScript evaluation for dynamic content extraction. Results are returned as structured data suitable for LLM processing and downstream analysis.","intents":["I want Claude to extract all product information from an e-commerce page","I need the AI to read and understand page text content for decision-making","I want to capture the current HTML state for debugging or archival","I need the agent to extract structured data (prices, dates, ratings) from a page"],"best_for":["Web scraping with content extraction and analysis","Price monitoring and competitive intelligence","Data extraction from structured web pages (job listings, real estate, etc.)","Page content analysis for accessibility or compliance checking"],"limitations":["Full-page HTML capture can be large (>10MB for complex pages); no built-in compression or streaming","Text extraction loses semantic structure (headings, lists, tables) — requires post-processing for layout-aware analysis","JavaScript evaluation is sandboxed to page context; cannot access external APIs or file system","Microdata/JSON-LD parsing requires valid markup; malformed structured data may fail silently","Dynamic content loaded after page load may not be captured without explicit wait commands"],"requires":["Active Playwright page instance","Page must be fully loaded (or explicitly waited for)","For JavaScript evaluation: valid JavaScript code that returns serializable data","For structured data extraction: page must contain valid JSON-LD or microdata markup"],"input_types":["extraction type (text, html, json-ld, custom-js)","CSS selector for scoped extraction","JavaScript code for custom evaluation","options (include-metadata, prettify-html, etc.)"],"output_types":["plain text content","HTML string","structured JSON (from JSON-LD or custom JS)","page metadata (title, description, canonical URL)","error messages for failed extraction"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm-executeautomation-playwright-mcp-server__cap_5","uri":"capability://image.visual.screenshot.and.visual.capture","name":"screenshot-and-visual-capture","description":"Captures visual snapshots of the current page or specific elements as PNG/JPEG images, with options for full-page capture, viewport-only capture, and element-specific screenshots. Images are returned as base64-encoded data or file paths, enabling visual feedback to LLMs and downstream vision models for page analysis and verification.","intents":["I want Claude to take a screenshot to verify that an action completed successfully","I need visual feedback on the current page state for debugging automation workflows","I want to capture specific UI elements for analysis by a vision model","I need to archive visual snapshots of pages for compliance or audit purposes"],"best_for":["Visual verification in automation workflows","Integration with vision models for page understanding","UI testing and visual regression detection","Debugging automation failures with visual context"],"limitations":["Full-page screenshots can be very large (>5MB for long pages); base64 encoding adds 33% overhead","Screenshots capture rendered pixels only; no access to underlying DOM or semantic structure","Element screenshots require precise bounding box calculation; off-screen or partially visible elements may not capture correctly","No built-in image compression or quality optimization — all images captured at full resolution","Screenshots are point-in-time snapshots; dynamic content changes between capture and analysis"],"requires":["Active Playwright page instance","Page must be rendered (headless or headed mode)","For element screenshots: valid element selector","Sufficient disk space or memory for image buffering"],"input_types":["capture type (full-page, viewport, element)","element selector for element-specific capture","image format (png, jpeg)","quality/compression options"],"output_types":["base64-encoded image data","file path to saved image","image metadata (width, height, format)"],"categories":["image-visual","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm-executeautomation-playwright-mcp-server__cap_6","uri":"capability://code.generation.editing.javascript.code.execution.in.page.context","name":"javascript-code-execution-in-page-context","description":"Executes arbitrary JavaScript code within the page context using Playwright's evaluate() API, enabling dynamic content extraction, page state manipulation, and custom logic execution. Code runs in the browser's JavaScript environment with access to the DOM, window object, and page-specific libraries, with results serialized back to the LLM as JSON.","intents":["I want Claude to execute custom JavaScript to extract data that's not easily accessible via selectors","I need the AI to manipulate page state (set form values, trigger events) programmatically","I want to evaluate complex page conditions (check if element has specific CSS class, validate form state)","I need the agent to interact with page-specific JavaScript libraries or APIs"],"best_for":["Complex data extraction from dynamic or JavaScript-heavy pages","Advanced page manipulation beyond standard click/type actions","Custom validation logic that requires page context","Integration with page-specific JavaScript APIs or libraries"],"limitations":["Executed code is sandboxed to page context; cannot access Node.js APIs, file system, or external networks","Return values must be JSON-serializable; functions, DOM nodes, and circular references will fail","No timeout control per evaluation; long-running scripts may block page interaction","Code injection attacks are possible if LLM-generated code is not validated; requires careful prompt engineering","Page-specific libraries may not be available or may have version conflicts"],"requires":["Active Playwright page instance","Valid JavaScript code as string","Return value must be JSON-serializable (primitives, objects, arrays)","Page context must be stable (no navigation during evaluation)"],"input_types":["JavaScript code as string","optional arguments to pass to code (serialized as JSON)","timeout value in milliseconds"],"output_types":["JSON-serialized return value","error message if code throws exception","undefined if code doesn't return value"],"categories":["code-generation-editing","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm-executeautomation-playwright-mcp-server__cap_7","uri":"capability://automation.workflow.browser.session.and.context.management","name":"browser-session-and-context-management","description":"Manages browser instances, pages, and contexts (isolated browser sessions with separate cookies, storage, and cache). Supports creating/closing browsers, managing multiple pages within a context, switching between contexts, and persisting/restoring browser state. Enables multi-user or multi-scenario automation workflows with isolated session management.","intents":["I want Claude to manage multiple independent browser sessions (e.g., testing different user accounts)","I need the AI to maintain session state across multiple pages (cookies, local storage)","I want to isolate automation scenarios to prevent cross-contamination","I need the agent to switch between different browser contexts or pages during a workflow"],"best_for":["Multi-user automation scenarios (testing different account types)","Parallel automation workflows requiring isolated sessions","Session persistence and recovery in long-running automation","Testing authentication flows with multiple user accounts"],"limitations":["Each browser instance consumes significant memory (300-500MB per Chromium instance); scaling to many concurrent browsers is resource-intensive","Context switching requires explicit tool calls; no automatic context detection or implicit switching","Browser state persistence (cookies, storage) requires manual serialization; no built-in state snapshots","No support for browser profiles or persistent user data directories — state is lost on browser close","Concurrent page operations within same context may have race conditions if not properly sequenced"],"requires":["Node.js 16+ with sufficient memory (1GB+ for multiple browser instances)","Playwright browser binaries (Chromium, Firefox, or WebKit)","MCP client capable of managing multiple concurrent connections"],"input_types":["browser type (chromium, firefox, webkit)","context options (viewport, user agent, locale, timezone)","page creation parameters","context/page identifiers for switching"],"output_types":["browser/context/page identifiers","success/failure status for operations","list of active contexts/pages","error messages for invalid operations"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm-executeautomation-playwright-mcp-server__cap_8","uri":"capability://automation.workflow.wait.and.synchronization.primitives","name":"wait-and-synchronization-primitives","description":"Provides tools for waiting on page conditions (element visibility, network idle, specific text appearance, custom conditions) with configurable timeouts and polling intervals. Enables reliable synchronization between LLM actions and page state changes, preventing race conditions and flaky automation by allowing explicit waits before proceeding with subsequent actions.","intents":["I want Claude to wait for a loading spinner to disappear before proceeding","I need the AI to wait for specific text to appear on the page (e.g., success message)","I want to ensure network requests complete before extracting data","I need the agent to wait for an element to become clickable before interacting with it"],"best_for":["Automation of dynamic pages with asynchronous content loading","Reliable form submission and validation workflows","Web scraping with variable page load times","Testing workflows requiring precise synchronization"],"limitations":["Timeout values are fixed per wait call; no adaptive timeouts based on historical page load times","Custom condition evaluation requires JavaScript code; no declarative condition syntax","Polling-based waits may miss transient state changes if polling interval is too large","No support for waiting on multiple conditions with OR logic; requires sequential waits","Network idle detection is heuristic-based and may not catch all background requests"],"requires":["Active Playwright page instance","Valid element selector or condition expression","Timeout value in milliseconds (default 30000)","For custom conditions: valid JavaScript code"],"input_types":["wait type (element-visible, element-hidden, text-appears, network-idle, custom)","element selector or text pattern","timeout in milliseconds","polling interval (optional)","JavaScript code for custom conditions"],"output_types":["success/failure status","time elapsed until condition met","error message if timeout exceeded","final page state after wait"],"categories":["automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm-executeautomation-playwright-mcp-server__cap_9","uri":"capability://automation.workflow.error.handling.and.recovery","name":"error-handling-and-recovery","description":"Implements error detection, logging, and recovery mechanisms for automation failures. Captures error context (stack traces, page state, screenshots), provides detailed error messages to LLMs, and supports retry logic with exponential backoff. Enables LLMs to reason about failures and attempt recovery without manual intervention.","intents":["I want Claude to detect when an action fails and retry with a different approach","I need detailed error information to understand why an automation step failed","I want the AI to capture page state (screenshot, HTML) when an error occurs for debugging","I need the agent to gracefully handle transient failures (network timeouts, temporary unavailability)"],"best_for":["Robust automation workflows requiring fault tolerance","Debugging complex automation failures with rich error context","Long-running automation tasks with transient failure handling","Production automation requiring detailed error logging and monitoring"],"limitations":["Error recovery is reactive; no proactive failure prediction or prevention","Retry logic is exponential backoff only; no support for custom retry strategies","Error context (screenshots, HTML) can be large; no built-in compression or selective capture","Error messages are generated by Playwright; may lack domain-specific context","No integration with external error tracking or alerting systems"],"requires":["Active Playwright page instance","Error handling enabled in MCP server configuration","Sufficient disk space for error logs and screenshots"],"input_types":["action to attempt with error handling","retry count and backoff strategy","error context options (capture-screenshot, capture-html, etc.)"],"output_types":["error message with type and stack trace","error context (screenshot, HTML, page state)","retry attempt count and status","recovery suggestion or fallback action"],"categories":["automation-workflow","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":44,"verified":false,"data_access_risk":"high","permissions":["Node.js 16+","Playwright 1.40+ (browser binaries: Chromium, Firefox, or WebKit)","MCP-compatible client (Claude Desktop, Cline, or custom MCP host)","System with sufficient memory for browser instances (minimum 512MB per browser)","Active Playwright browser instance","Valid URL format (http/https)","Network connectivity to target domain","MCP client capable of handling async navigation responses","Node.js 16+ with MCP SDK","MCP-compatible client (Claude Desktop 0.1+, Cline, or custom host)"],"failure_modes":["No built-in retry logic for flaky network conditions — requires client-side implementation","Single browser instance per MCP server connection — concurrent automation requires multiple server instances","Playwright's inherent limitations apply: no support for Flash, Java applets, or legacy ActiveX controls","MCP protocol overhead adds ~50-200ms latency per command compared to direct Playwright SDK usage","No native support for proxy rotation or IP spoofing — must be configured at OS/network level","No built-in handling for popup windows or new browser contexts — requires explicit context management","Timeout values are fixed or require reconfiguration; no dynamic timeout adjustment based on page complexity","Navigation waits only for 'load' or 'networkidle' states — doesn't detect custom JavaScript-based readiness signals","Cannot distinguish between intentional redirects and error pages without additional DOM inspection","MCP protocol overhead adds ~50-200ms latency per tool call compared to direct SDK usage","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.6329645183153843,"quality":0.32,"ecosystem":0.52,"match_graph":0.25,"freshness":0.52,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.15,"match_graph":0.23,"freshness":0.12}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:23.902Z","last_scraped_at":"2026-05-03T14:04:47.472Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":73079,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=executeautomation-playwright-mcp-server","compare_url":"https://unfragile.ai/compare?artifact=executeautomation-playwright-mcp-server"}},"signature":"P/a0PLB1kBBqPNeybHkUK2Yu89jS73WWKXjNxv2kUCSOyJdpLh8w9S0cNWsuzaQ08XfnO0sRAMY5xU926ZxPCQ==","signedAt":"2026-06-20T08:19:03.754Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/executeautomation-playwright-mcp-server","artifact":"https://unfragile.ai/executeautomation-playwright-mcp-server","verify":"https://unfragile.ai/api/v1/verify?slug=executeautomation-playwright-mcp-server","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}