{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"npm_npm-iflow-mcppuppeteer-mcp-server","slug":"npm-iflow-mcppuppeteer-mcp-server","name":"@iflow-mcp/puppeteer-mcp-server","type":"mcp","url":"https://www.npmjs.com/package/@iflow-mcp/puppeteer-mcp-server","page_url":"https://unfragile.ai/npm-iflow-mcppuppeteer-mcp-server","categories":["mcp-servers"],"tags":[],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"npm_npm-iflow-mcppuppeteer-mcp-server__cap_0","uri":"capability://tool.use.integration.headless.browser.automation.via.mcp","name":"headless-browser-automation-via-mcp","description":"Exposes Puppeteer's headless browser control as an MCP server, allowing LLM clients to spawn, navigate, and interact with Chromium instances through standardized tool calls. Implements the Model Context Protocol to translate high-level browser actions (navigate, click, type, screenshot) into Puppeteer API calls, enabling multi-turn browser automation workflows driven by LLM reasoning without direct SDK integration in the client.","intents":["I want my LLM agent to autonomously browse websites and extract data without writing custom Puppeteer code","I need to automate web scraping, form filling, or testing workflows triggered by Claude or other MCP-compatible LLMs","I want to build a browser-automation-as-a-service backend that LLMs can call via standardized tool protocols"],"best_for":["LLM application developers building agents that need web interaction capabilities","Teams integrating browser automation into Claude-based workflows via MCP","Builders prototyping autonomous web scraping or testing agents"],"limitations":["No built-in session persistence — each MCP call operates within a single browser context; multi-step workflows require the LLM to maintain state across calls","Puppeteer's headless mode limitations apply: no support for WebRTC, some media playback scenarios, and certain browser APIs unavailable in headless contexts","Experimental status means API surface may change; no guaranteed backward compatibility between versions","Single-browser-instance design — concurrent requests from multiple LLM clients may queue or conflict; no native multi-instance pooling","Network latency between MCP server and client adds overhead for screenshot/DOM inspection operations"],"requires":["Node.js 14+ (Puppeteer requirement)","Chromium or Chrome browser binary (Puppeteer downloads automatically or uses system installation)","MCP-compatible client (Claude, or custom LLM application with MCP support)","Network connectivity between MCP client and server"],"input_types":["URL strings","CSS selectors or XPath expressions","Text input for form fields","Keyboard/mouse action specifications"],"output_types":["PNG/JPEG screenshots","HTML DOM snapshots","Extracted text content","JSON-structured page metadata"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-iflow-mcppuppeteer-mcp-server__cap_1","uri":"capability://data.processing.analysis.dom.inspection.and.element.selection","name":"dom-inspection-and-element-selection","description":"Provides tools to query and inspect the current page's DOM structure, returning element metadata (selectors, text content, attributes, visibility state) that enable LLMs to identify and target specific UI elements for interaction. Uses Puppeteer's page.evaluate() to execute JavaScript in the browser context, extracting structured element information and computing CSS/XPath selectors for reliable element targeting across page navigation.","intents":["I need my LLM agent to understand the structure of a webpage and identify which elements to interact with","I want to extract specific text, links, or form fields from a page and return them as structured data","I need to find elements by text content, class, or other attributes when CSS selectors are not stable"],"best_for":["Web scraping agents that need to dynamically locate and extract content","Testing automation where element selectors may vary across page versions","LLM-driven form-filling workflows requiring robust element identification"],"limitations":["JavaScript-dependent — elements rendered by client-side frameworks may not be fully populated until JS execution completes; timing issues can cause stale DOM snapshots","Selector stability not guaranteed — dynamically-generated class names or IDs may change between page loads, requiring fallback strategies","Large DOM trees (10k+ elements) can cause performance degradation in serialization and transmission","Shadow DOM and iframe content requires special handling; not all nested elements may be accessible via standard DOM queries"],"requires":["Active browser page context from headless-browser-automation-via-mcp","JavaScript execution enabled in Puppeteer (default)"],"input_types":["CSS selectors","XPath expressions","Text content patterns","Element attribute filters"],"output_types":["JSON array of element metadata (selector, text, attributes, position)","HTML snippet of matched elements","Computed CSS selector strings"],"categories":["data-processing-analysis","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-iflow-mcppuppeteer-mcp-server__cap_2","uri":"capability://image.visual.screenshot.and.visual.capture","name":"screenshot-and-visual-capture","description":"Captures the current viewport or full-page screenshots as PNG/JPEG images, optionally with element highlighting or region clipping. Implements Puppeteer's page.screenshot() with configurable viewport dimensions, device emulation, and clip regions, enabling LLMs to visually inspect page state and verify automation outcomes without relying solely on DOM inspection.","intents":["I want my LLM agent to take a screenshot to verify that a page loaded correctly or an action succeeded","I need to capture specific regions of a page for visual analysis or debugging","I want to emulate different device viewports (mobile, tablet, desktop) and capture responsive layouts"],"best_for":["Visual verification in browser automation workflows","Testing agents that need to assert visual correctness","Debugging LLM-driven automation by inspecting rendered output"],"limitations":["Screenshot generation adds latency (typically 200-500ms per capture) and memory overhead for large pages","Image transmission over MCP adds bandwidth cost; no built-in compression or progressive loading","Headless rendering may differ from headed browser rendering (fonts, animations, some CSS effects)","Full-page screenshots of very tall pages (10k+ pixels) can consume significant memory and produce large files"],"requires":["Active browser page context","Sufficient memory for image buffer allocation","MCP client capable of receiving and processing binary image data"],"input_types":["Viewport dimensions (width, height)","Device emulation profile (mobile, tablet, desktop)","Clip region coordinates (x, y, width, height)","Image format preference (png, jpeg)"],"output_types":["PNG image buffer","JPEG image buffer","Base64-encoded image string"],"categories":["image-visual","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-iflow-mcppuppeteer-mcp-server__cap_3","uri":"capability://automation.workflow.page.navigation.and.url.control","name":"page-navigation-and-url-control","description":"Manages browser navigation including goto(), back(), forward(), and reload() operations with configurable wait conditions (waitUntil: 'load', 'domcontentloaded', 'networkidle'). Implements Puppeteer's navigation API with timeout handling and error reporting, enabling LLMs to traverse multi-page workflows and handle navigation failures gracefully.","intents":["I want my LLM agent to navigate to a specific URL and wait for the page to fully load before proceeding","I need to handle browser back/forward navigation in multi-step workflows","I want to reload a page and retry operations if they fail due to network issues"],"best_for":["Multi-page web scraping workflows requiring sequential navigation","Testing agents that simulate user navigation patterns","LLM-driven workflows with conditional branching based on page content"],"limitations":["Navigation timeouts are fixed per call; no adaptive timeout based on page complexity","Redirect chains may not be fully resolved if intermediate pages trigger JavaScript navigation","Network errors during navigation may leave the browser in an inconsistent state; no automatic recovery","waitUntil conditions may not work reliably for SPAs (Single Page Applications) that don't trigger traditional load events"],"requires":["Active browser context","Network connectivity to target URLs","Timeout configuration (default typically 30s)"],"input_types":["URL string (http/https)","Wait condition enum (load, domcontentloaded, networkidle)","Timeout duration in milliseconds"],"output_types":["Navigation success/failure status","Final URL after redirects","HTTP status code","Error message if navigation failed"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-iflow-mcppuppeteer-mcp-server__cap_4","uri":"capability://automation.workflow.user.interaction.simulation","name":"user-interaction-simulation","description":"Simulates user interactions including click(), type(), press() (keyboard), hover(), and focus() operations on page elements. Implements Puppeteer's input APIs with selector-based targeting, allowing LLMs to trigger form submissions, button clicks, and keyboard navigation without direct JavaScript injection. Supports both CSS selector and XPath targeting for element location.","intents":["I want my LLM agent to fill out and submit web forms by typing into fields and clicking buttons","I need to simulate keyboard navigation (Tab, Enter, Escape) for accessibility testing","I want to trigger hover states or focus events to reveal dynamic UI elements"],"best_for":["Form automation and data entry workflows","Testing agents validating interactive UI behavior","Web scraping workflows requiring interaction to load dynamic content"],"limitations":["Selector-based targeting requires stable element selectors; dynamic or obfuscated selectors may fail","Type() operation is character-by-character and slower than direct value assignment; may not trigger all input events","No support for drag-and-drop, file uploads, or complex gesture interactions","Timing-sensitive interactions (rapid clicks, double-clicks) may be unreliable due to network latency between MCP client and server","JavaScript-triggered event handlers may not fire if elements are not in the viewport or are obscured"],"requires":["Active browser page context","Valid CSS selector or XPath for target element","Element must be visible and interactive (not disabled, not hidden)"],"input_types":["CSS selector or XPath string","Text input for type() operation","Keyboard key names (Enter, Tab, Escape, etc.)","Coordinates for click() operation"],"output_types":["Interaction success/failure status","Error message if element not found or interaction failed"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-iflow-mcppuppeteer-mcp-server__cap_5","uri":"capability://data.processing.analysis.content.extraction.and.text.parsing","name":"content-extraction-and-text-parsing","description":"Extracts text content, HTML, and structured data from the current page using Puppeteer's page.evaluate() to execute JavaScript queries. Supports extracting all text, specific element text, HTML snippets, and running custom JavaScript to parse page content. Returns extracted content as plain text, HTML, or JSON-structured data depending on the extraction query.","intents":["I want my LLM agent to extract all text from a page for summarization or analysis","I need to parse structured data (product listings, search results) from a page and return it as JSON","I want to extract specific HTML sections for further processing or storage"],"best_for":["Web scraping workflows extracting content for analysis or storage","LLM-driven content aggregation and summarization","Data extraction from semi-structured web pages"],"limitations":["Custom JavaScript extraction requires the LLM to write or the server to support templated queries; no automatic schema inference","Large pages with extensive text may produce output exceeding MCP message size limits; no built-in pagination","Dynamically-loaded content (infinite scroll, lazy loading) may not be captured unless explicitly scrolled and waited for","Encoding issues may occur with non-UTF8 content or special characters; no automatic normalization"],"requires":["Active browser page context","JavaScript execution enabled","Sufficient memory for content buffering"],"input_types":["CSS selector for element targeting","JavaScript code snippet for custom extraction","Extraction mode enum (text, html, json)"],"output_types":["Plain text string","HTML string","JSON object or array","Structured data with metadata"],"categories":["data-processing-analysis","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-iflow-mcppuppeteer-mcp-server__cap_6","uri":"capability://automation.workflow.page.wait.and.synchronization","name":"page-wait-and-synchronization","description":"Provides tools to wait for specific conditions before proceeding: waitForSelector() (element appears), waitForNavigation() (page navigation completes), waitForFunction() (custom JavaScript condition), and waitForTimeout() (fixed delay). Implements Puppeteer's wait APIs with configurable timeouts, enabling LLMs to synchronize automation steps with asynchronous page behavior (AJAX requests, animations, dynamic content loading).","intents":["I want my LLM agent to wait for a specific element to appear before interacting with it","I need to wait for a page navigation to complete after clicking a link","I want to wait for a custom condition (e.g., 'loading spinner disappears') before proceeding"],"best_for":["Automation workflows with asynchronous page behavior (SPAs, AJAX-heavy sites)","Testing agents that need to synchronize with dynamic content loading","Workflows requiring robust timing without hardcoded delays"],"limitations":["Timeout-based waiting can mask underlying issues; if a condition never occurs, the agent must handle timeout errors","Custom JavaScript conditions (waitForFunction) require the LLM to write valid JavaScript; syntax errors will cause failures","No built-in exponential backoff or retry logic; timeouts are fixed per call","Waiting for multiple conditions simultaneously is not supported; must be sequential","Network-dependent conditions (waitForNavigation) may timeout if navigation is blocked or redirected unexpectedly"],"requires":["Active browser page context","Timeout configuration (default typically 30s)","For waitForFunction: valid JavaScript code"],"input_types":["CSS selector (for waitForSelector)","JavaScript code snippet (for waitForFunction)","Timeout duration in milliseconds","Navigation options (for waitForNavigation)"],"output_types":["Success/timeout status","Element reference (for waitForSelector)","Error message if condition not met"],"categories":["automation-workflow","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-iflow-mcppuppeteer-mcp-server__cap_7","uri":"capability://automation.workflow.browser.context.and.session.management","name":"browser-context-and-session-management","description":"Manages browser lifecycle including launching, closing, and resetting browser contexts. Implements Puppeteer's browser and page lifecycle APIs, allowing LLMs to control when browser instances are created/destroyed and manage session state (cookies, local storage, authentication). Supports context isolation for parallel workflows or test isolation.","intents":["I want to launch a fresh browser instance for a new automation workflow","I need to preserve session state (cookies, auth tokens) across multiple page navigations","I want to reset the browser to a clean state between test runs"],"best_for":["Multi-step automation workflows requiring session persistence","Testing agents that need isolated browser contexts","Workflows with authentication or stateful interactions"],"limitations":["Single-instance design means concurrent workflows may queue or conflict; no native multi-instance pooling","Browser launch time (typically 1-3s) adds latency to workflow initialization","Memory usage grows with browser instance lifetime; no automatic garbage collection or memory limits","Session state (cookies, local storage) is not persisted across server restarts; requires external storage for durability","No support for browser profiles or persistent user data directories in the current implementation"],"requires":["Node.js process with sufficient memory (typically 100-200MB per browser instance)","Chromium/Chrome binary available","Permissions to spawn child processes"],"input_types":["Browser launch options (headless, viewport, user agent)","Context isolation flags"],"output_types":["Browser instance ID","Session state metadata","Launch success/failure status"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":29,"verified":false,"data_access_risk":"high","permissions":["Node.js 14+ (Puppeteer requirement)","Chromium or Chrome browser binary (Puppeteer downloads automatically or uses system installation)","MCP-compatible client (Claude, or custom LLM application with MCP support)","Network connectivity between MCP client and server","Active browser page context from headless-browser-automation-via-mcp","JavaScript execution enabled in Puppeteer (default)","Active browser page context","Sufficient memory for image buffer allocation","MCP client capable of receiving and processing binary image data","Active browser context"],"failure_modes":["No built-in session persistence — each MCP call operates within a single browser context; multi-step workflows require the LLM to maintain state across calls","Puppeteer's headless mode limitations apply: no support for WebRTC, some media playback scenarios, and certain browser APIs unavailable in headless contexts","Experimental status means API surface may change; no guaranteed backward compatibility between versions","Single-browser-instance design — concurrent requests from multiple LLM clients may queue or conflict; no native multi-instance pooling","Network latency between MCP server and client adds overhead for screenshot/DOM inspection operations","JavaScript-dependent — elements rendered by client-side frameworks may not be fully populated until JS execution completes; timing issues can cause stale DOM snapshots","Selector stability not guaranteed — dynamically-generated class names or IDs may change between page loads, requiring fallback strategies","Large DOM trees (10k+ elements) can cause performance degradation in serialization and transmission","Shadow DOM and iframe content requires special handling; not all nested elements may be accessible via standard DOM queries","Screenshot generation adds latency (typically 200-500ms per capture) and memory overhead for large pages","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.05,"quality":0.41,"ecosystem":0.3,"match_graph":0.25,"freshness":0.6,"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":"2026-05-24T12:16:23.903Z","last_scraped_at":"2026-04-22T08:09:48.453Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=npm-iflow-mcppuppeteer-mcp-server","compare_url":"https://unfragile.ai/compare?artifact=npm-iflow-mcppuppeteer-mcp-server"}},"signature":"Ds31dNWoPS8GgtipfpZ7eTftWM66Zl/ZbyMnvayq8Bz5ld2UlY/rbkz3xjIZb+z7GxMNYzeODFaPGSRw1bvrCw==","signedAt":"2026-06-21T07:50:57.551Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/npm-iflow-mcppuppeteer-mcp-server","artifact":"https://unfragile.ai/npm-iflow-mcppuppeteer-mcp-server","verify":"https://unfragile.ai/api/v1/verify?slug=npm-iflow-mcppuppeteer-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"}}