Scrapeless Weekly Changelog: August 24–30, 2026 Updates

TL;DR:

• TikTok Scraper is officially available. Public documentation now covers creator profiles, creator video lists, and TikTok Shop product details.
• Scrapeless MCP Server now includes LLM Chat Scraper. The new tool brings AI-answer collection into MCP-connected workflows.
• Google AI Mode now accepts a URL as input. A complete AI Mode access link can replace the usual prompt-based input parameters.
• Search and AI collection received reliability updates. Google Search API has a new release, several LLM scrapers have higher success rates, and Amazon Rufus responses include improved source-reference parsing.

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TikTok Scraper has moved from preview to official release. During August 24–30, Scrapeless also added LLM Chat Scraper to its MCP Server and introduced URL-based collection for Google AI Mode. The release includes Google Search API improvements for larger commercial workloads, better AI scraper success rates, and richer Amazon Rufus source data.

💥 TikTok Scraper Is Officially Live

TikTok Scraper now has public API documentation for three collection tasks:

Capability	Actor	Typical Use Case
Creator profiles	scraper.tiktok.user.detail	Research public creator profiles
Creator video lists	scraper.tiktok.user.work	Track a creator’s published content
TikTok Shop product details	scraper.tiktok.shop.page	Collect product-page data for commerce research

Teams can now use the published request and response references to build integrations. The separate actors let developers choose the data source their workflow needs, whether that is a creator profile, a content list, or a product page.

For creator-data projects, keep collection limited to public information and store only the fields needed for the project. Public availability does not remove the need to review platform terms and applicable data-handling requirements.

💫 LLM Chat Scraper Joins Scrapeless MCP Server

Scrapeless MCP Server now exposes llm_chat_scraper for creating AI-answer collection tasks. The Scrapeless MCP Server tool reference lists support for ChatGPT, Gemini, Perplexity, Copilot, Google AI Mode, Google AI Overview, Grok, and Alexa.

This gives MCP-connected agents a direct tool for requesting AI-engine data alongside the server’s existing search, browser, and crawling capabilities. A research workflow can use the collected answers for engine comparisons or recurring AI-visibility monitoring.

MCP clients discover named tools and their input schemas through the MCP tool-discovery interface. Check the tool list exposed by your connected server before adding the new action to a workflow. The Scrapeless MCP Server overview explains the broader integration.

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🌟 Google AI Mode Supports URL-Based Input

Google AI Mode Scraper now accepts a url string containing a complete Google AI Mode access link. This adds an input option for workflows that already have an AI Mode URL.

The Google AI Mode input reference specifies an important rule: when url is supplied, the other input parameters are not required and are ignored if included. Do not expect a separate prompt, country, shopping, or location setting to override the supplied URL.

Pass the complete link rather than rebuilding it from selected pieces. If your application parses or stores the link, preserve its query component and encoding using the behavior defined by the URL Standard.

⬆️ Service Improvements

Google Search API Updated for Larger Workloads

Google Search API received a new release focused on large-scale commercial use, with improved stability and data completeness. The update supports teams running recurring search-data collection for monitoring, research, and production applications.

Higher Success Rates Across AI Scrapers

Copilot, Perplexity, and Gemini received success-rate improvements for Austria (AT). Google AI Overview also received a success-rate improvement. These are qualitative service updates; results still depend on the engine, request, and collection context.

Amazon Rufus Source References Are Parsed More Fully

Amazon Rufus Scraper now parses additional source-reference fields from responses. The added information helps teams inspect references associated with Rufus answers and carry that context into downstream analysis. Process source data when it is present rather than assuming every answer includes references.

Conclusion

This week’s release makes TikTok collection available through documented actors, adds AI-answer collection to MCP, and gives Google AI Mode a URL-based input path. Search reliability and Rufus source parsing also improve the data available to downstream workflows.

Choose the relevant actor from the Scrapeless Scraping API, and review Scrapeless pricing when planning your workload.

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