ScholarFetch FAQs

Name: ScholarFetch
Author: laibniz

Question 1

Which academic engines does ScholarFetch integrate with?

Accepted Answer

ScholarFetch integrates with major scholarly APIs including Elsevier (Scopus), OpenAlex, Crossref, arXiv, Europe PMC, Springer Nature, and Semantic Scholar for comprehensive data retrieval and enrichment.

Question 2

What is ScholarFetch and what does it do?

Accepted Answer

ScholarFetch is a command-line interface (CLI) and MCP server tool that aggregates academic paper metadata, abstracts, and reading links from multiple scholarly APIs. It enables unified search, author investigation, DOI lookup, and abstract retrieval to enhance research workflows.

Question 3

Is there a web interface or demo available for ScholarFetch?

Accepted Answer

Yes, a live web demo is available at a Hugging Face Space (https://huggingface.co/spaces/Laibniz/ScholarFetch_Web), which also hosts a public MCP streamable HTTP endpoint for the tool.

Question 4

How does ScholarFetch improve the precision and recall of academic searches?

Accepted Answer

It improves recall through parallel retrieval and deduplication across multiple providers, and enhances precision with DOI-first retrieval, cross-engine enrichment, and robust author disambiguation workflows.

Question 5

Can ScholarFetch be used for automation or with LLM agent systems?

Accepted Answer

Yes, ScholarFetch is designed to be agent-ready. It includes classic MCP and FastMCP servers, allowing seamless integration into LLM systems, automation pipelines, and other agent builders.

ScholarFetch

ScholarFetch

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