Open-source Deep Research

Searching Zhihu from your AI Agent

Use Zhihu answers as cited Chinese context inside broader agent research.

Question-answer context for agents

Zhihu often captures expert-style explanations, product comparisons, and user concerns. AutoSearch lets agents query Zhihu in a research loop, collect cited answers, and compare them with formal docs or international discussion.

Chinese perspectives stay visible

English-only research can miss regional reasoning and terminology. AutoSearch includes Zhihu alongside other Chinese and global channels, helping agents understand how a topic is framed across languages and communities.

Better synthesis from mixed sources

Zhihu is strongest when interpreted with other evidence. AutoSearch can combine it with WeChat, Xiaohongshu, GitHub, papers, and social channels, giving agents a cited source set for more balanced summaries.

How it fits

AutoSearch places Zhihu inside an MCP-native research workflow. Your agent can ask for Chinese expert discussion, then AutoSearch gathers cited Zhihu results plus related sources from 40 channels. The agent uses that evidence to produce a brief, compare viewpoints, or plan follow-up research. This is useful when questions involve China markets, technical adoption, product perception, or policy interpretation.

Try this prompt

Search Zhihu for views on AI coding assistants in China.
Compare cited answers with GitHub and Hacker News discussions.