VibeScholar FAQs

Question 1

Which AI assistants are compatible with VibeScholar?

Accepted Answer

VibeScholar is designed as an MCP (Model Context Protocol) server, making it fully compatible with Claude (via Claude Code) and any other AI assistant or client that supports the MCP standard.

Question 2

How does VibeScholar access academic papers and their content?

Accepted Answer

It leverages headless Chromium for extensive Google Scholar search, enriching results with Semantic Scholar metadata like stable IDs and full abstracts. Full-text PDFs are then resolved via a four-source cascade and read directly into memory.

Question 3

What is VibeScholar's main purpose?

Accepted Answer

VibeScholar transforms AI assistants into powerful academic research partners, providing them with advanced tools for comprehensive literature search, reading, and navigation across academic papers.

Question 4

Does VibeScholar save full-text PDFs locally?

Accepted Answer

By default, `fetch_paper` extracts text in memory and discards the PDF. You can use the `save_paper` tool to explicitly download a local copy or `index_papers` to add a folder of PDFs to your searchable local corpus.

Question 5

Can VibeScholar search my personal collection of PDFs?

Accepted Answer

Yes, VibeScholar includes an optional local corpus mode. You can index folders of your own PDFs and search them using a sophisticated hybrid system combining FAISS semantic and FTS5 keyword retrieval, enhanced with cross-encoder reranking.

VibeScholar

VibeScholar

Características Principales

Casos de Uso

Características Principales

Casos de Uso