Open-source Deep Research

Open-source Deep Research for Academia

Track papers, code, and research community signals from one agent workflow.

Papers and code together

Academic work often depends on both publications and implementation evidence. AutoSearch can combine arXiv, GitHub, Hugging Face, technical blogs, and forum discussions, helping researchers see whether ideas have working code, benchmarks, and active adoption.

Citations for lab handoffs

Research assistants and graduate teams need findings that can be checked later. AutoSearch returns cited outputs, making it easier to hand off literature scans, weekly digests, and related-work notes without losing source provenance.

Chinese sources expand coverage

Important implementation notes and model discussions may appear in Chinese technical communities. AutoSearch includes 10+ Chinese sources, allowing academic teams to monitor multilingual signals alongside English papers and repositories.

How it fits

AutoSearch fits into academic workflows as an MCP-native research companion. Your agent host can ask for a literature scan, code survey, or community digest. AutoSearch gathers cited evidence across papers, repositories, technical forums, video channels, and Chinese platforms, then returns material for the researcher to evaluate. It helps with discovery and synthesis prep, while methodology, interpretation, and scholarly claims remain under human control.

Try this prompt

Find the last month of papers and code about small language model agents.
Group by method, benchmark, and open-source implementation with citations.