cv-cat/spider_xhs

小红书爬虫数据采集,小红书逆向,私信,直播,小红书全域运营解决方案

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Summary Information

Updated 2 minutes ago
Added to GitGenius on September 8th, 2026
Created on August 8th, 2023
Open Issues & Pull Requests: 122 (+0)
GitHub issues: Enabled
Number of forks: 1,309
Total Stargazers: 7,607 (+1)
Total Subscribers: 33 (+0)

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Detailed Description

Spider_XHS is a web scraper and content management tool for the Xiaohongshu platform that enables data collection and automated publishing.

The project addresses the absence of complete content operations APIs from Xiaohongshu by reverse-engineering the platform's signature algorithms and HTTP interfaces. It reconstructs authentication parameters used by the PC client and creator platform, including a1, web_id, b1, websectiga, sec_poison_id, gid, x-s, x-t, x-s-common, x-b3-traceid, x-xray-traceid, x-rap-param, search_id, request_id, sign, and q-signature. The tool wraps these core interfaces to handle data collection from the PC interface, content publishing through the creator platform, and KOL data access via the Dandelion system, allowing developers to integrate AI models for bulk content collection, rewriting, and one-click publishing workflows.

Developers considering adoption should understand this is positioned as infrastructure for AI-driven content operations rather than a general-purpose scraper. It suits teams building automated content management systems that require stable read and write access to Xiaohongshu data. The project explicitly states it is for learning and exchange only, with commercial use prohibited. The README does not compare this tool to alternatives.

The project maintains active development with regular updates to handle platform changes. The codebase includes multi-account binding and management features with support for QR code login, phone verification, and cookie import, along with encrypted cookie storage and automatic health checks. The tool provides AI-powered image optimization capabilities for content preparation. Documentation and examples are provided to guide integration with AI systems.