AnyCrawl

Exposes web scraping capabilities through the Model Context Protocol (MCP), enabling Claude, Cursor, and other LLM clients to invoke scraping operations as native tools without HTTP polling or custom integrations. Implements MCP resource and tool handlers that translate LLM function calls into scraping directives, managing request/response serialization and error handling within the MCP message protocol.

Parses fetched HTML documents using a DOM-aware parser (likely Cheerio or similar) and extracts structured content via CSS selectors, XPath expressions, or heuristic-based content detection. Supports both explicit selector-based extraction and automatic content identification for common patterns (articles, tables, lists), returning cleaned text or structured JSON representations.

Implements client-side rate limiting with configurable requests-per-second limits, adaptive backoff based on HTTP 429/503 responses, and optional integration with target site's robots.txt crawl-delay directives. Tracks request history per domain and automatically throttles subsequent requests if rate limits are detected.

Maintains an in-memory or persistent cache of scraped content keyed by URL, with configurable TTL (time-to-live) and cache invalidation strategies. Deduplicates requests for the same URL within a session or across sessions, reducing redundant network requests and improving performance for repeated scraping patterns.

Optionally uses a headless browser engine (Puppeteer, Playwright, or similar) to render JavaScript-heavy pages before scraping, enabling extraction from single-page applications and dynamically-loaded content. Manages browser lifecycle, page navigation, and DOM state changes, with configurable wait conditions (network idle, element visibility, custom timeouts) to ensure content is fully loaded before extraction.

Processes multiple URLs in parallel with configurable concurrency limits, implementing exponential backoff retry logic for failed requests and automatic handling of HTTP errors (429, 503, timeouts). Maintains crawl state and progress tracking, allowing resumption of interrupted crawls and deduplication of already-fetched URLs within a session.

Allows configuration of HTTP headers (User-Agent, Accept-Language, Referer, custom headers) to mimic different browsers, devices, or API clients. Supports rotating User-Agent strings and header profiles to avoid detection by anti-bot systems, with preset profiles for common browsers and devices.

Post-processes extracted content to remove boilerplate (navigation, ads, footers), normalize whitespace and encoding, and optionally convert to Markdown format. Uses heuristic-based or DOM-based approaches to identify main content areas and strip irrelevant elements, improving signal-to-noise ratio for downstream LLM processing.

Automatically extracts metadata (title, description, author, publish date, image URLs) from HTML pages using Open Graph, Twitter Card, Schema.org, and other semantic markup standards. Returns structured JSON with extracted metadata alongside content, enabling LLM clients to access both raw content and machine-readable attributes.

Manages HTTP cookies and session state across multiple requests, allowing scraping of pages that require authentication or maintain user sessions. Supports cookie jar persistence, manual cookie injection, and optional integration with headless browser sessions for login workflows.

Supports routing HTTP requests through configurable proxy servers (HTTP, HTTPS, SOCKS5) or VPN connections, enabling geographic spoofing, IP rotation, and circumvention of IP-based rate limiting. Integrates with proxy services and allows per-request proxy selection.

Implements multi-level error handling with fallback strategies: if JavaScript rendering fails, falls back to static HTML parsing; if extraction with selectors fails, attempts heuristic content detection; if a URL is unreachable, returns cached content if available. Provides detailed error reporting with categorized failure reasons (network, parsing, timeout, blocked).