# Academic search

Google Scholar MCP Server is an interface service that provides AI assistants with access to academic papers on Google Scholar through the Model Context Protocol (MCP). It supports keyword search, advanced retrieval, and author information query functions to help AI models retrieve academic paper metadata.

MCP-DBLP is a service based on the Model Context Protocol (MCP) that provides large language models with the ability to access the DBLP computer science literature database, including functions such as search, citation processing, and BibTeX export.

The arXiv Research Assistant MCP Server is a local server built on Python and the FastMCP framework, specifically designed to interact with the arXiv.org paper database. It provides functions such as keyword search, getting the latest papers by category, querying paper details, retrieving author papers, and supports generating paper summaries and comparison prompts to help users efficiently explore academic literature.

An MCP server for interacting with the Crossref API, providing functions to search for literature by title and author and obtain literature details through DOI.

This is an implementation of the scientific search MCP protocol designed for the Cursor editor, integrating multiple academic search engines (such as Google Scholar, PubMed, arXiv, etc.), supporting Semantic Scholar search through Tor, and providing functions such as PDF processing.

The Crossref MCP Server is a bridge service that provides academic paper metadata search for AI assistants through the Model Context Protocol (MCP). It supports retrieving information on academic literatures, journals, and funding institutions in the Crossref database by DOI, title, or keywords.

An MCP server based on Node.js that uses Express and Axios to proxy queries to the OpenAlex API and supports Docker deployment.

The Sci-Hub MCP service is a bridge connecting AI assistants with Sci-Hub's academic resources, providing functions such as paper search, metadata acquisition, and PDF download through the Model Context Protocol.

This project implements an MCP server that interacts with the Semantic Scholar API, providing functions such as paper search, obtaining paper/author details, and querying cited literature.

The arXiv MCP Server is a service based on the Model Context Protocol (MCP) that allows users to interact with the arXiv API using natural language, enabling functions such as retrieving academic article metadata, downloading PDF files, searching the database, and loading articles into the context of a large - language model (LLM).

Open Search MCP is a comprehensive model context protocol server that provides 33 professional search and research tools, covering multiple domains such as academia, development, and privacy search, with enterprise - level security features and standardized output.

A Google Scholar search and analysis tool based on the MCP protocol, providing paper search and scholar profile analysis functions, and supporting integration with MCP clients and Cherry Studio.