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ArXiv Research Intelligence MCP Server

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    • F
      license
      Not graded
      quality
      D
      maintenance
      Enables LLMs to search arXiv, extract and analyze paper content, and build a personal semantically-searchable research library with saved papers and notes.
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    • A
      license
      A
      quality
      D
      maintenance
      Enables searching, downloading, and managing academic papers from arXiv.org through natural language interactions. Provides tools for paper discovery, PDF downloads, and local paper collection management.
      4
      1
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables AI assistants to search, retrieve, and manage a personal arXiv paper library over MCP, with explainable relevance ranking, trend analysis, saved papers, and reading suggestions — all running locally without accounts or external services.
      MIT
    • A
      license
      A
      quality
      B
      maintenance
      Enables local literature workflows by searching arXiv, retrieving paper metadata, downloading and parsing PDFs, and retrieving page-cited body evidence for Q&A. It also exposes usage resources and templates for searching, analyzing, and summarizing papers via stdio MCP.
      4
      MIT
    • A
      license
      A
      quality
      C
      maintenance
      Enables an AI assistant to search scientific literature across OpenAlex and Semantic Scholar, download supported Elsevier and Springer Nature full texts, and build a local searchable index so questions can be answered with citations to original paper passages. It runs locally over stdio with CPU-based embeddings and needs no Qdrant account, Docker, GPU, or LLM API key of its own.
      11
      MIT
    • A
      license
      Not graded
      quality
      D
      maintenance
      Enables arXiv paper search, PDF download, text extraction, and context chunking for LLM pipelines, along with advanced features like citation graphs and reproducibility scoring.
      2
      MIT