Paper Search FAQs

Question 1

Is Paper Search suitable for automating scientific literature reviews?

Accepted Answer

Absolutely. By enabling LLMs to programmatically search and fetch academic papers from multiple sources with standardized data, Paper Search is an excellent tool for automating parts of scientific literature reviews, data collection for meta-analyses, and AI-driven research.

Question 2

What is Paper Search and what does it do?

Accepted Answer

Paper Search is a Python-based Model Context Protocol (MCP) server designed to help Large Language Models (LLMs) search and download academic papers. It integrates with platforms like arXiv, PubMed, bioRxiv, and Semantic Scholar, providing standardized research data.

Question 3

Which academic platforms can I search and download papers from using Paper Search?

Accepted Answer

Currently, Paper Search supports searching and downloading from arXiv, PubMed, bioRxiv, medRxiv, Google Scholar, IACR ePrint Archive, and Semantic Scholar. Its design is extensible, allowing for the easy addition of more sources in the future.

Question 4

What kind of output does Paper Search provide?

Accepted Answer

Paper Search outputs retrieved paper information in a consistent dictionary format through its `Paper` class. This standardized output is ideal for further processing by LLMs or other automated research workflows.

Question 5

How does Paper Search integrate with AI models like ChatGPT or Claude?

Accepted Answer

Paper Search provides standardized `search` and `fetch` tools compatible with OpenAI Deep Research and ChatGPT connectors. It uses the Model Context Protocol (MCP) for seamless integration with LLM clients like Claude Desktop, enhancing their context and research capabilities.

Paper Search

Paper Search

Key Features

Use Cases

Key Features

Use Cases