Arxiv MCP Server
The arXiv Research Assistant MCP Server is a local server built based 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 in categories, querying paper details, author search, trend analysis, etc., and supports generating paper summaries and comparison prompts, facilitating users to efficiently explore academic literature.
rating : 2 points
downloads : 6.4K
What is the arXiv Research Assistant?
This is an intelligent paper assistant designed specifically for researchers and students, which allows for quick access to millions of academic papers on arXiv.org. It can help you find papers by keywords, authors, or categories, and provides paper details and comparison functions.How to use the arXiv Research Assistant?
You can interact with the server directly through Claude AI, or use it via the command-line tool after running the local server. The main functions include paper search, detail viewing, and paper comparison.Use cases
Suitable for academic research, literature reviews, tracking the latest developments in the field, finding papers by specific authors, and quickly comparing the content of related papers.Main functions
Keyword search
Find relevant papers by keywords, and sort them by relevance or time
Latest papers in categories
Get the latest list of papers in specific subject areas (e.g., cs.AI, math.AP)
Paper details
Get the complete metadata of a paper, including title, authors, abstract, etc., through the arXiv ID
Author search
Find all papers published by a specific author
Trend analysis (experimental)
Get an overview of popular keywords and topics in the subject area
Summary prompt generation
Automatically generate optimized prompts to help AI better summarize the paper content
Comparison prompt generation
Generate structured comparison prompts for two papers to facilitate the analysis of similarities and differences
Advantages
Connect directly to the arXiv database to obtain the latest paper information
Support multiple search methods to meet different research needs
Provide intelligent prompt generation to optimize the AI-assisted research experience
Lightweight design with high operating efficiency
Limitations
The trend analysis function currently uses simulated data
Basic technical knowledge is required for local installation
Some advanced functions are still under development
How to use
Install the server
Automatically install via Smithery or manually install from PyPI
Start the server
Run the server program
Configure Claude AI
Add the server configuration in Claude's MCP settings
Start using
Interact with the arXiv Research Assistant through the Claude AI interface
Usage examples
Find the latest AI papers
Track the latest research progress in the field of artificial intelligence
Research a specific topic
Conduct in-depth research on relevant literature on a specific topic
Author research overview
Understand the research achievements of a certain author
Paper comparison
Compare the similarities and differences between two related papers
Frequently asked questions
How to know the category code of a certain subject?
Is there a limit to the number of search results?
What is the data source for the trend analysis function?
Does the server need to be continuously connected to the Internet?
Does it support exporting search results?
Related resources
arXiv official website
Open access academic paper platform
FastMCP framework documentation
The technical framework used by the server
Smithery installation guide
One-click installation service
GitHub repository
Project source code

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