Scrapeless Weekly Changelog: August 17–23, 2026 Updates

TL;DR:

• TikTok Scraper is coming soon. Planned coverage includes creator profiles, creator work lists, and TikTok Shop product details.
• Fanout query data is now supported across three AI engines. ChatGPT, Gemini, and Perplexity support the capability, with corresponding documentation now available.
• Scrapeless MCP Server has a new Crawl tool. MCP-connected agents can launch broader crawling workflows through the same tool interface.
• ChatGPT and Grok collection is more reliable. Service-side improvements strengthen stability without requiring customer-facing request changes.

---

This week’s release expands how teams can collect social-commerce data, analyze AI answer paths, and connect crawling to agent workflows. From August 17–23, Scrapeless prepared TikTok Scraper for release, added fanout query support across three AI engines, introduced Crawl in Scrapeless MCP Server, and improved ChatGPT and Grok stability.

💥 Coming Soon: TikTok Scraper

TikTok Scraper is the first highlight this week. The upcoming actors are designed to help teams collect public creator and commerce data without maintaining a separate browser workflow for each page type.

Planned coverage includes:

• Creator profiles for retrieving public account and profile details.
• Creator work lists for collecting a creator’s published content list.
• TikTok Shop product details for extracting structured information from supported product pages.

The public documentation is still being prepared, so request parameters, response fields, and general availability will be announced separately. Teams evaluating these workflows should collect only public data and apply their own compliance, retention, and access policies.

💫 Fanout Query Support for ChatGPT, Gemini, and Perplexity

scraper.chatgpt, scraper.gemini, and scraper.perplexity now support fanout query data, and the corresponding documentation has been published.

Fanout data helps teams examine the related query paths generated during an AI answer workflow. It can support answer-engine monitoring, prompt research, content-gap analysis, and downstream discovery pipelines across multiple engines.

Because availability can depend on the returned answer, integrations should check that fanout data is present before processing it. Review the relevant LLM Chat Scraper documentation before updating a production parser.

🌟 A New Crawl Tool for Scrapeless MCP Server

Scrapeless MCP Server now includes a Crawl tool, extending agent workflows beyond single-page retrieval. MCP-connected applications can use the tool to initiate broader crawling tasks while keeping data collection inside the same server integration.

This fits the MCP tool model: servers expose named functions that models can discover and invoke, as described in the official MCP tools specification. The specification also defines input schemas for tool parameters and optional output schemas for structured results. Developers building clients can consult the MCP schema reference, while the official example servers demonstrate common integration patterns.

Start Scraping with Scrapeless

Power up your web scraping and automation workflow with Scrapeless!
Sign up today and get $5 in free credit — no credit card required.

Claim your free credit now in the Scrapeless Dashboard.

⬆️ Service Reliability Improvements

More Stable ChatGPT Collection

scraper.chatgpt received service-side stability improvements that reduce interrupted collection and improve successful-result delivery. Existing integrations do not need a new request parameter to benefit from the update.

Grok State-Handling Fix

scraper.grok received a service-side state-handling fix for invalid sessions. The change improves collection continuity and reduces empty or interrupted workflows without changing the customer-facing actor call.

👀 What This Means for Developers

This release strengthens three parts of a modern data workflow. TikTok Scraper will add focused social-commerce coverage, fanout query data provides another way to study AI answer behavior, and the MCP Crawl tool makes broader collection available to agent-driven applications. Reliability work on ChatGPT and Grok supports more dependable recurring jobs.

Explore the LLM Chat Scraper, see five ways to use Scrapeless MCP Server, or review Scrapeless pricing when planning a production workload.

Conclusion

The August 17–23 release previews TikTok Scraper, adds fanout query support across ChatGPT, Gemini, and Perplexity, brings Crawl to Scrapeless MCP Server, and improves ChatGPT and Grok reliability.

Ready to Build Your Next Data Workflow?

Join developers building AI-answer monitoring, agent automation, and public-web data pipelines in the Scrapeless community: Discord · Telegram.

Sign up at app.scrapeless.com and start building with Scrapeless.