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The system constrains all viewport dimensions to maximum 1072x1072 to ensure each tile fits within optimal vision model input boundaries without requiring external image resizing or post-processing.","intents":["I need to capture a full website screenshot and have Claude analyze it without hitting token limits","I want to screenshot long-form pages and automatically split them into vision-model-friendly chunks","I need to ensure screenshots are optimized for Claude's vision capabilities without manual tiling"],"best_for":["AI developers building Claude-integrated web automation agents","Teams building vision-based web testing and monitoring systems","Developers integrating screenshot capture into MCP-compatible AI development environments"],"limitations":["Fixed 1072x1072 tile size cannot be customized — designed specifically for Claude Vision API constraints","Tiling process adds latency proportional to page height (full-page screenshots of 10,000px+ pages may take 5-10 seconds)","Sharp image processing requires sufficient system memory for large pages; very large pages (50MB+) may cause memory pressure"],"requires":["Node.js ≥20.0.0","Chromium/Chrome browser (headless mode)","Sharp image processing library (included in dependencies)"],"input_types":["URL string","viewport width/height integers (constrained to max 1072)"],"output_types":["PNG images (base64-encoded or file paths)","Array of tiled PNG chunks with coordinate metadata"],"categories":["image-visual","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-just-every-mcp-screenshot-website-fast__cap_1","uri":"capability://automation.workflow.configurable.wait.strategies.for.dynamic.content.stabilization","name":"configurable wait strategies for dynamic content stabilization","description":"Implements multiple wait strategies (networkIdle, domContentLoaded, custom JavaScript conditions) to ensure dynamic content has fully loaded before capture, with configurable timeouts and retry logic. The system injects JavaScript probes to detect application-specific readiness conditions (e.g., React hydration, data fetch completion) rather than relying solely on browser network events.","intents":["I need to screenshot a React/Vue/Angular app and wait for it to fully hydrate before capturing","I want to capture a page only after specific JavaScript conditions are met (e.g., 'window.appReady === true')","I need to handle pages with lazy-loaded content and ensure all visible content is rendered"],"best_for":["Developers testing single-page applications with complex initialization","Teams building web scraping agents that need to handle dynamic content","QA automation engineers validating rendered state of JavaScript-heavy applications"],"limitations":["Custom JavaScript condition detection requires knowledge of application internals; generic 'wait for element' patterns may not work across different frameworks","Timeout-based waits add latency (default 30 seconds) — slow or unresponsive pages will hit timeout and capture incomplete state","No built-in detection for infinite loading states; pages that continuously fetch data will timeout rather than capture partial state"],"requires":["Node.js ≥20.0.0","Chromium/Chrome in headless mode","For custom conditions: understanding of target application's JavaScript API"],"input_types":["URL string","waitStrategy enum: 'networkIdle' | 'domContentLoaded' | 'custom'","customWaitCondition: JavaScript code string (optional)"],"output_types":["Boolean (wait succeeded/failed)","Screenshot PNG after wait condition satisfied"],"categories":["automation-workflow","image-visual"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-just-every-mcp-screenshot-website-fast__cap_10","uri":"capability://data.processing.analysis.sharp.based.image.processing.and.tiling.pipeline","name":"sharp-based image processing and tiling pipeline","description":"Uses the Sharp image processing library to efficiently tile full-page screenshots into 1072x1072 chunks, handling image format conversion, compression, and metadata extraction. The tiling pipeline processes captured PNG images through Sharp's streaming API, splitting large images into overlapping or non-overlapping tiles based on configuration, and returning tile metadata with coordinate information.","intents":["I need to split a full-page screenshot into vision-model-friendly chunks efficiently","I want to process images with minimal memory overhead using streaming","I need tile metadata (coordinates, dimensions) to reconstruct or analyze the full page"],"best_for":["Developers building vision model integration pipelines","Teams processing large images with memory constraints","Engineers optimizing image processing performance"],"limitations":["Sharp tiling is synchronous and CPU-bound — processing very large images (50MB+) may block the event loop for 1-2 seconds","Tile coordinate metadata is generated but not automatically used for reconstruction — consumers must implement their own reassembly logic","No built-in support for overlapping tiles or padding — tiles are strictly non-overlapping"],"requires":["Node.js ≥20.0.0","Sharp library (included in dependencies)","Sufficient system memory for image buffering (typically 2-3x image size)"],"input_types":["PNG image buffer or file path","Tile size: 1072x1072 (fixed)","Image dimensions: width, height"],"output_types":["Array of tile buffers (PNG format)","Tile metadata: { x, y, width, height, index }","Total tile count and coverage information"],"categories":["data-processing-analysis","image-visual"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-just-every-mcp-screenshot-website-fast__cap_2","uri":"capability://automation.workflow.headless.browser.lifecycle.management.with.auto.restart.and.signal.handling","name":"headless browser lifecycle management with auto-restart and signal handling","description":"Manages Chromium browser process lifecycle with automatic restart on crash, graceful shutdown on signals (SIGTERM, SIGINT), and connection pooling to reuse browser instances across multiple screenshot operations. The system implements a serve-restart wrapper that monitors the main MCP server process and automatically restarts it if it crashes, maintaining availability for long-running AI agent workflows.","intents":["I need a screenshot service that stays alive across multiple requests without manual restart","I want the browser to automatically recover from crashes in production deployments","I need graceful shutdown handling so in-flight screenshot operations complete before process termination"],"best_for":["Production deployments of MCP screenshot servers integrated with Claude or other AI agents","Long-running automation workflows that make hundreds of screenshot requests","Teams deploying screenshot services in containerized environments (Docker, Kubernetes)"],"limitations":["Auto-restart mechanism adds ~2-5 second overhead on crash recovery; rapid successive crashes may cause cascading restarts","Browser connection pooling is in-process only — no distributed caching across multiple server instances","Signal handling requires proper process management; if parent process doesn't propagate signals, graceful shutdown may not trigger"],"requires":["Node.js ≥20.0.0","Chromium/Chrome binary available on system PATH or via PUPPETEER_EXECUTABLE_PATH","For MCP mode: proper signal handling in parent process (e.g., systemd, Docker, PM2)"],"input_types":["Process signals (SIGTERM, SIGINT)","Screenshot requests (URL, viewport, wait strategy)"],"output_types":["Screenshot PNG","Process exit code (0 for clean shutdown, non-zero for error)"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-just-every-mcp-screenshot-website-fast__cap_3","uri":"capability://image.visual.screencast.recording.with.adaptive.frame.rates.and.webp.animation","name":"screencast recording with adaptive frame rates and webp animation","description":"Records time-series screenshots of page interactions as WebP animations with adaptive frame rate selection based on content change detection. The system captures PNG frames at configurable intervals, deduplicates identical frames to reduce file size, and encodes the sequence into WebP animations using Sharp, enabling efficient video-like capture of dynamic page behavior without full video codec overhead.","intents":["I need to record a page interaction (e.g., form submission, animation) as a video for analysis","I want to capture page state changes over time and encode them as an efficient WebP animation","I need to detect when page content has changed and only capture frames when something new happens"],"best_for":["QA automation engineers recording test execution flows","Developers building interactive web testing agents that need to verify animations and transitions","Teams creating visual regression testing systems with time-series capture"],"limitations":["WebP animation encoding is CPU-intensive; recording 10+ seconds of content may take 30+ seconds to encode","Frame deduplication logic is pixel-perfect comparison — minor rendering differences (anti-aliasing, sub-pixel changes) may not be detected as duplicates","No audio capture — screencast is visual-only, suitable for page state changes but not for capturing audio interactions"],"requires":["Node.js ≥20.0.0","Chromium/Chrome in headless mode","Sharp library with WebP support (included)","Duration parameter (in milliseconds) for how long to record"],"input_types":["URL string","duration: integer (milliseconds)","interval: integer (milliseconds between frames, optional)","JavaScript injection code (optional)"],"output_types":["WebP animation file","PNG frame sequence (intermediate)","Metadata: frame count, duration, deduplication stats"],"categories":["image-visual","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-just-every-mcp-screenshot-website-fast__cap_4","uri":"capability://data.processing.analysis.javascript.console.message.capture.with.execution.context","name":"javascript console message capture with execution context","description":"Captures console output (log, error, warn, info) during page execution with full execution context, including message content, severity level, and timestamp. The system injects a JavaScript listener that intercepts console methods and collects messages over a specified duration, returning structured JSON with all captured messages for analysis by AI models.","intents":["I need to capture JavaScript errors and warnings that occur during page load for debugging","I want to extract console logs from a page execution to understand application behavior","I need to correlate console messages with screenshot captures to understand what went wrong"],"best_for":["Developers debugging JavaScript errors in automated web testing","Teams building AI agents that need to understand application state via console output","QA engineers analyzing application behavior through console logs"],"limitations":["Only captures console methods (log, error, warn, info) — does not capture unhandled promise rejections or global error handlers unless explicitly logged","Console capture is limited to the page's execution context — cannot capture messages from iframes or cross-origin resources","Large volumes of console output (1000+ messages) may impact page performance during capture"],"requires":["Node.js ≥20.0.0","Chromium/Chrome in headless mode","Duration parameter (milliseconds) for how long to collect console messages"],"input_types":["URL string","duration: integer (milliseconds)","wait strategy (optional, to ensure page is ready before capturing)"],"output_types":["JSON array of console messages","Each message: { level: 'log'|'error'|'warn'|'info', message: string, timestamp: number }"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-just-every-mcp-screenshot-website-fast__cap_5","uri":"capability://tool.use.integration.mcp.protocol.integration.with.stdio.json.rpc.transport","name":"mcp protocol integration with stdio json-rpc transport","description":"Exposes screenshot and screencast capabilities as MCP tools via stdio-based JSON-RPC transport, enabling integration with Claude Code, VS Code, Cursor, and JetBrains IDEs. The system implements the Model Context Protocol specification, serializing tool requests/responses as JSON-RPC messages over stdin/stdout, allowing AI assistants to invoke screenshot operations as native tools.","intents":["I want Claude to be able to take screenshots as part of its reasoning process","I need to integrate screenshot capabilities into my MCP-compatible IDE (VS Code, Cursor, JetBrains)","I want to expose screenshot tools to an AI agent via the Model Context Protocol"],"best_for":["AI developers building Claude-integrated workflows in Claude Code or compatible IDEs","Teams deploying MCP servers for AI agent integration","Developers extending AI assistant capabilities with web automation"],"limitations":["stdio transport is single-process only — no built-in support for multiple concurrent clients","JSON-RPC serialization adds ~50-100ms overhead per request compared to direct function calls","Tool definitions must be pre-declared in MCP server startup; dynamic tool registration is not supported"],"requires":["Node.js ≥20.0.0","MCP-compatible client (Claude Code, VS Code with MCP extension, Cursor, JetBrains)","Proper stdio configuration in client's MCP server settings"],"input_types":["JSON-RPC request with method name and parameters","Tool invocation from MCP client"],"output_types":["JSON-RPC response with result or error","Screenshot PNG (base64-encoded in JSON response)"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-just-every-mcp-screenshot-website-fast__cap_6","uri":"capability://automation.workflow.cli.binary.interface.with.direct.command.line.screenshot.execution","name":"cli binary interface with direct command-line screenshot execution","description":"Provides a command-line interface (bin/mcp-screenshot-website.js) for direct screenshot capture without MCP server overhead, enabling scripting, testing, and manual screenshot operations. The CLI accepts URL, viewport, wait strategy, and output format parameters, executing the screenshot capture engine directly and returning results as files or base64-encoded output.","intents":["I need to take a quick screenshot from the command line for testing or debugging","I want to script screenshot capture in a shell script or CI/CD pipeline","I need to capture screenshots without running an MCP server"],"best_for":["Developers testing screenshot functionality locally","DevOps engineers integrating screenshot capture into CI/CD pipelines","Teams building shell-based automation scripts"],"limitations":["CLI mode does not support concurrent requests — each invocation spawns a new browser process, adding ~2-3 second startup overhead","No persistent browser connection — each CLI invocation creates and destroys a browser instance, making it inefficient for batch operations","Output is limited to file or base64 encoding; no streaming or chunked response support"],"requires":["Node.js ≥20.0.0","Chromium/Chrome binary available on system PATH","Executable permissions on bin/mcp-screenshot-website.js"],"input_types":["Command-line arguments: --url, --viewport, --wait-strategy, --output-format"],"output_types":["PNG file (written to disk)","Base64-encoded PNG (printed to stdout)","JSON metadata (optional)"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-just-every-mcp-screenshot-website-fast__cap_7","uri":"capability://automation.workflow.viewport.configuration.with.constraint.enforcement","name":"viewport configuration with constraint enforcement","description":"Allows configuration of browser viewport dimensions (width, height) with automatic constraint enforcement to ensure all viewports are clamped to maximum 1072x1072 pixels. The system validates viewport parameters at request time and rejects or clamps oversized viewports to maintain compatibility with Claude Vision API tiling constraints.","intents":["I want to capture screenshots at different viewport sizes (mobile, tablet, desktop) while maintaining vision API compatibility","I need to ensure all screenshots fit within Claude Vision API constraints regardless of requested viewport","I want to test responsive design at multiple breakpoints with automatic constraint enforcement"],"best_for":["Developers testing responsive web design across multiple viewport sizes","Teams building cross-device testing automation","QA engineers validating layout at different screen sizes"],"limitations":["Maximum viewport is hard-clamped to 1072x1072 — cannot capture at higher resolutions even if requested","Viewport constraints are applied uniformly; no per-axis scaling or aspect ratio preservation","Responsive design testing is limited to viewport sizes under 1072px — cannot test desktop layouts at full resolution"],"requires":["Node.js ≥20.0.0","Chromium/Chrome in headless mode","Viewport width and height as integers"],"input_types":["viewport.width: integer (0-1072)","viewport.height: integer (0-1072)"],"output_types":["Validated viewport configuration","Screenshot at specified viewport dimensions"],"categories":["automation-workflow","image-visual"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-just-every-mcp-screenshot-website-fast__cap_8","uri":"capability://data.processing.analysis.base64.and.file.based.output.encoding.with.format.selection","name":"base64 and file-based output encoding with format selection","description":"Supports multiple output formats for screenshot results: base64-encoded PNG for embedding in JSON responses (suitable for MCP protocol), and file-based PNG output for CLI and direct file storage. The system handles encoding/decoding transparently based on output format selection, enabling flexible integration with different transport mechanisms.","intents":["I need to embed screenshots in JSON responses for MCP protocol transmission","I want to save screenshots to disk for local analysis or archival","I need to support both embedded and file-based output depending on the use case"],"best_for":["MCP server implementations that need to embed images in JSON-RPC responses","CLI users who want to save screenshots to disk","Teams supporting multiple output formats for different integration scenarios"],"limitations":["Base64 encoding increases payload size by ~33% compared to binary PNG — large screenshots may exceed JSON-RPC message size limits","File-based output requires write permissions to the target directory; no built-in permission handling or fallback","No streaming or chunked encoding — entire image must be loaded into memory before encoding"],"requires":["Node.js ≥20.0.0","For file output: write permissions to output directory","For base64 output: sufficient memory for image buffering"],"input_types":["outputFormat: 'base64' | 'file'","outputPath: string (for file output)"],"output_types":["Base64-encoded PNG string (for base64 format)","File path string (for file output)"],"categories":["data-processing-analysis","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-just-every-mcp-screenshot-website-fast__cap_9","uri":"capability://automation.workflow.page.navigation.with.retry.logic.and.error.recovery","name":"page navigation with retry logic and error recovery","description":"Implements robust page navigation with automatic retry on transient failures, timeout handling, and detailed error reporting. The system attempts to navigate to the target URL with configurable retry counts and backoff strategies, capturing detailed error information (network errors, timeouts, navigation failures) for debugging and fallback handling.","intents":["I need to reliably navigate to a URL even if the first attempt fails due to network issues","I want automatic retry logic for transient failures without manual intervention","I need detailed error information when navigation fails to understand what went wrong"],"best_for":["Developers building resilient web automation agents","Teams deploying screenshot services in unreliable network environments","QA engineers testing error handling in screenshot capture workflows"],"limitations":["Retry logic uses exponential backoff which adds latency (default: 1s, 2s, 4s for 3 retries) — total navigation time can exceed 10 seconds for failing URLs","No built-in circuit breaker — will continue retrying permanently failing URLs up to retry limit","Timeout handling is global; cannot configure per-URL timeouts or adaptive timeout strategies"],"requires":["Node.js ≥20.0.0","Chromium/Chrome in headless mode","Network connectivity to target URL"],"input_types":["URL string","retryCount: integer (optional, default 3)","timeout: integer milliseconds (optional, default 30000)"],"output_types":["Navigation success/failure status","Error details: { code, message, retryCount, totalTime }","Screenshot after successful navigation"],"categories":["automation-workflow","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":32,"verified":false,"data_access_risk":"high","permissions":["Node.js ≥20.0.0","Chromium/Chrome browser (headless mode)","Sharp image processing library (included in dependencies)","Chromium/Chrome in headless mode","For custom conditions: understanding of target application's JavaScript API","Sharp library (included in dependencies)","Sufficient system memory for image buffering (typically 2-3x image size)","Chromium/Chrome binary available on system PATH or via PUPPETEER_EXECUTABLE_PATH","For MCP mode: proper signal handling in parent process (e.g., systemd, Docker, PM2)","Sharp library with WebP support (included)"],"failure_modes":["Fixed 1072x1072 tile size cannot be customized — designed specifically for Claude Vision API constraints","Tiling process adds latency proportional to page height (full-page screenshots of 10,000px+ pages may take 5-10 seconds)","Sharp image processing requires sufficient system memory for large pages; very large pages (50MB+) may cause memory pressure","Custom JavaScript condition detection requires knowledge of application internals; generic 'wait for element' patterns may not work across different frameworks","Timeout-based waits add latency (default 30 seconds) — slow or unresponsive pages will hit timeout and capture incomplete state","No built-in detection for infinite loading states; pages that continuously fetch data will timeout rather than capture partial state","Sharp tiling is synchronous and CPU-bound — processing very large images (50MB+) may block the event loop for 1-2 seconds","Tile coordinate metadata is generated but not automatically used for reconstruction — consumers must implement their own reassembly logic","No built-in support for overlapping tiles or padding — tiles are strictly non-overlapping","Auto-restart mechanism adds ~2-5 second overhead on crash recovery; rapid successive crashes may cause cascading restarts","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.05,"quality":0.47,"ecosystem":0.49999999999999994,"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":"2026-06-17T09:51:03.577Z","last_scraped_at":"2026-05-03T14:00:15.503Z","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=just-every-mcp-screenshot-website-fast","compare_url":"https://unfragile.ai/compare?artifact=just-every-mcp-screenshot-website-fast"}},"signature":"ob/6c75WSIHky0pJ0cNQTGITlQUlfsDQC63odFWEvqCMoR6T7YDLMFadZDRRCuPuJwacky7x7UXzO+fSHkYeCg==","signedAt":"2026-06-21T10:19:22.613Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/just-every-mcp-screenshot-website-fast","artifact":"https://unfragile.ai/just-every-mcp-screenshot-website-fast","verify":"https://unfragile.ai/api/v1/verify?slug=just-every-mcp-screenshot-website-fast","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"}}