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Import and retrieve local paper PDFs with section-aware academic RAG search.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "ScholarAgent RAG MCP Server" yet — see the docs or source repo.
Import the paper PDFs in my specified folder into ScholarAgent RAG MCP Server. After indexing, tell me each paper's title, section structure, and retrieval status.
A summary of import and indexing results, including paper list, section details, and retrieval readiness.
Search the local paper library for content about 'transformer efficiency'. Prefer relevant passages from the methods and experiments sections, and label each with the paper title and section name.
Relevant paper chunks with source labels, organized by section for further analysis or citation.
Extract key passages related to 'RAG chunking strategy' from indexed papers and format them as context suitable for Claude Code or Codex.
A concise set of paper context snippets, ready to pass to an MCP client, with source information included.
Search papers, parse full-text PDFs, extract details, and manage citations.
Search, retrieve, and answer questions from PDF documents with RAG.
Ingest PDFs, run semantic search, and answer questions with source citations.
Convert research PDFs to Markdown and search them with grep plus semantics.
Analyze local paper PDFs rigorously and generate editable maps and research insights.
Index and semantically search code, PDFs, and documents with exact citations.