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Extract structured data from academic PDFs with natural-language querying and batch workflows.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "paper-extraction-MCP" yet — see the docs or source repo.
Extract the title, authors, publication year, research question, methods, datasets, and main findings from this academic PDF, and return them in JSON.
A structured JSON output containing core metadata and a summary of the paper’s research content.
Process all paper PDFs in this folder in batch, extract the research domain, method type, experimental subjects, and conclusions for each paper, and compile them into a table.
A summary table that makes it easy to compare topics, methods, and results across papers.
After reading this paper, answer: What model did the authors use? What baselines were included? How much did performance improve? Provide concise answers and cite the relevant passages.
Concise answers to the questions, along with the supporting passages or locations from the paper.
Extract text, images, and tables from PDFs with multilingual analysis.
Extract text and metadata from PDFs via URL or Base64 input.
Convert research PDFs to Markdown and search them with grep plus semantics.
Lets AI inspect PDF text layers, outlines, and page content locally.
Enable AI to read PDFs, extract content, and search specific information.
Search papers, parse full-text PDFs, extract details, and manage citations.