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Embodied Paper Notes MCP

Embodied Paper Notes MCP

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    • A
      license
      A
      quality
      C
      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
    • F
      license
      A
      quality
      D
      maintenance
      Enables searching, downloading, and reading academic papers from multiple platforms including arXiv, Semantic Scholar, PubMed, bioRxiv, medRxiv, IACR, Google Scholar, RePEc/IDEAS, and Sci-Hub with PDF to Markdown conversion.
      29
      7
      -
    • 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
      C
      maintenance
      Enables searching arXiv and Semantic Scholar, fetching and extracting paper text page by page, and retrieving cited excerpts or optionally synthesized answers to questions about papers. It caches results locally and provides PDF page citations for verification.
      MIT
    • A
      license
      Not graded
      quality
      C
      maintenance
      Enables academic research through one stdio server that searches, reads, and relates papers from a large research index, searches multiple paper providers with PDF retrieval and Markdown conversion, and optionally searches a local Markdown corpus with hybrid retrieval and claim comparison. A unified search tool queries all three sources at once while preserving per-source errors.
      MIT