literature-review-toolslisted

Recommend AND run open-source AI tools, agents, Claude Code / Codex skills, and MCP servers for any stage of a literature review — searching, reading, extracting, synthesizing, screening, citation-checking, and paper writing. Use when the user asks "what tool should I use to..." OR "install/run/use <tool> to ..." for research/lit-review work: automating a survey or related-work section, PDF→Markdown extraction for LLMs (MinerU/marker/docling), PRISMA / systematic review (ASReview), citation-backed Q&A over PDFs (PaperQA2), wiring papers into Claude/Cursor via MCP (arxiv/paper-search/zotero servers), or chatting with a Zotero library. Also answers direct literature lookups — find papers on a topic, resolve a DOI, get an open-access PDF, check a citation, search PubMed / OpenAlex / Crossref / Semantic Scholar / Europe PMC / arXiv — with no install and no API key. Ships a launcher (scripts/litrun.py) that installs each tool in an isolated venv and runs it, plus keyless bundled scripts for multi-source search and
brycewang-stanford/lit-review-agent-tools · ★ 13 · AI & Automation · score 74

Install: claude install-skill brycewang-stanford/lit-review-agent-tools

# Literature Review Tools — Select & Run A curated, use-case-organized catalog of the strongest **open-source** AI tools for literature review — **plus a launcher that actually installs and runs the top ones.** Covers: end-to-end research agents, deep-research / auto-survey generators, autonomous "idea→paper" systems, citation-backed RAG over PDFs, PRISMA screening, MCP servers, Zotero/Obsidian integrations, PDF→structured extraction, citation graphs, and paper-writing / peer-review assistants. Full source of truth (README, always current star counts): <https://github.com/brycewang-stanford/lit-review-agent-tools> ## Three modes - **Look up** — user wants *the literature itself*: "find papers on X", "get me the PDF for this DOI", "does this citation exist", "what does PubMed have since 2022". Answer it directly — no install, no key. Start with [`reference/apis/README.md`](reference/apis/README.md) for one-off lookups, or run the bundled `papers-fetch` / `oa-resolve` scripts for anything corpus-sized. - **Recommend** — user asks "what should I use to …". Route with the tables below; cite the catalog for details. - **Run** — user asks to *install / run / use* a specific tool ("turn this PDF into Markdown with MinerU", "ask PaperQA2 about these papers", "set up the arXiv MCP server"). Drive [`scripts/litrun.py`](scripts/litrun.py) via Bash — do not hand the user raw pip commands to copy. Mode 1 is the cheap default. Do not send someone to install PyTorch when they asked for