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Using Google Scholar for Conducting Deep and Critical Literature Reviews

  • Why this server?

    Provides a biomedical literature annotation and relationship mining server based on PubTator3, offering convenient access through the MCP interface, useful for specialized literature review.

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    🔍 A biomedical literature annotation and relationship mining server based on PubTator3, providing convenient access through the MCP interface.
    Python
    MIT License
    • Linux
    • Apple
  • Why this server?

    Provides Claude and other LLMs with read-only access to Hugging Face Hub APIs, enabling interaction with models, datasets, spaces, papers, and collections, broadening the scope of accessible research materials.

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    A Model Context Protocol server that provides Claude and other LLMs with read-only access to Hugging Face Hub APIs, enabling interaction with models, datasets, spaces, papers, and collections through natural language.
    4
    Python
    MIT License
    • Apple
  • Why this server?

    Specifically designed to enable AI assistants to search and access Google Scholar papers through a simple MCP interface, directly addressing the user's request.

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    🔍 Enable AI assistants to search and access Google Scholar papers through a simple MCP interface.
    2
    Python
    • Linux
    • Apple
  • Why this server?

    This tool extends AI clients to provide access to arXiv and Hugging Face papers, assisting with literature review tasks such as discussing papers, searching for new research, and organizing literature reviews.

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    MCP Extension that gives LLMs access to arXiv and Hugging Face papers, enabling users to discuss papers, search for new research, and organize literature reviews through natural conversation.
    3
    Python
    MIT License
    • Apple
  • Why this server?

    Provides a bridge between AI models and academic research by enabling precise paper searches and access to full paper content, facilitating AI's ability to engage with scientific literature. Focuses on pre-prints.

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    The ArXiv MCP Server bridges the gap between AI models and academic research by providing a sophisticated interface to arXiv's extensive research repository. This server enables AI assistants to perform precise paper searches and access full paper content, enhancing their ability to engage with scientific literature.
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    Python
    Apache 2.0
    • Linux
    • Apple
  • Why this server?

    Enables searching and retrieving research articles from PubMed with a focus on open access content and full-text link retrieval.

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    An MCP server implementation that enables searching and retrieving research articles from PubMed with specific focus on open access content filtering and full-text link retrieval.
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    3
    JavaScript
  • Why this server?

    This tool enables the AI to access IETF RFC documents. Very useful for technical research.

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    A Model Context Protocol server that enables Large Language Models to search and access IETF RFC documents with pagination support.
    Python
    MIT License
  • Why this server?

    This tool fetches and processes documentation using vector search, enabling AI assistants to augment their responses with relevant documentation context.

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    A Model Context Protocol (MCP) server that enables semantic search and retrieval of documentation using a vector database (Qdrant). This server allows you to add documentation from URLs or local files and then search through them using natural language queries.
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    JavaScript
    Apache 2.0
    • Apple
  • Why this server?

    Allows AI assistants to access research papers and related code implementations from PapersWithCode, which enhances literature review by linking research with practical code examples.

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    A server that allows AI assistants to search for research papers, read their content, and access related code repositories through the PapersWithCode API.
    3
    Python
  • Why this server?

    Enables semantic search, image search, and cross-modal search functionalities through integration with Jina AI's neural search capabilities, which can be beneficial for finding diverse sources of information during literature reviews.

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    Enables semantic search, image search, and cross-modal search functionalities through integration with Jina AI's neural search capabilities.
    1
    JavaScript
    MIT License