Arxiv MCP Server

🚀 arXiv MCP Server

An MCP (Model Context Protocol) server that provides tools for interacting with the arXiv API to search and retrieve academic papers.

🚀 Quick Start

This server implements the Model Context Protocol to offer tools for searching and retrieving papers from the arXiv preprint repository. It enables AI assistants to search for papers using various criteria, obtain details about specific papers, conduct category - based searches, and extract full - text content from PDFs.

✨ Features

• Search Papers: Search for papers using various criteria (title, author, abstract, category, etc.).
• Get Paper Details: Obtain detailed information about a specific paper by its arXiv ID.
• Category Search: Search for papers in a specific arXiv category.
• PDF Content Extraction: Download and extract full - text content from paper PDFs.
• Structured Results: Returns properly parsed JSON data instead of raw XML.
• Caching: Intelligent PDF caching to avoid redundant downloads.

📦 Installation

Prerequisites

• Node.js 18+
• npm or pnpm

Setup

1. Clone this repository:

   git clone https://github.com/your-username/arxiv-mcp-server.git
   cd arxiv-mcp-server
   

2. Install dependencies:

   npm install
   

3. Build the project:

   npm run build
   

💻 Usage Examples

As an MCP Server

Start the server:

npm start

The server will run on stdio, allowing it to communicate with MCP clients.

MCP Client Configuration

Add this configuration to your MCP client settings. For Claude Desktop, add to your claude_desktop_config.json:

{
  "mcpServers": {
    "arxiv": {
      "name": "arxiv-mcp-server",
      "command": "node",
      "args": ["build/index.js"],
      "cwd": "C:/path/to/arxiv-mcp-server",
      "enabled": true,
      "alwaysAllow": [
        "search_papers",
        "get_paper",
        "search_by_category",
        "get_paper_content"
      ],
      "env": {}
    }
  }
}

For other MCP clients, use a similar configuration structure. Make sure to:

• Update the cwd path to point to your arxiv - mcp - server directory.
• Ensure the build/index.js file exists (run npm run build first).
• The alwaysAllow array lists tools that won't require user confirmation.

Available Tools

search_papers

Search for papers on arXiv by various criteria with flexible query options.

Parameters:

• query (string, optional): General search query across all fields.
• category (string, optional): arXiv category (e.g., cs.AI, physics.optics).
• author (string, optional): Author name to search for.
• title (string, optional): Words to search for in the title.
• abstract (string, optional): Words to search for in the abstract.
• start (number, optional): Starting index for pagination (0 - based, default: 0).
• max_results (number, optional): Maximum number of results to return (max 2000, default: 10).
• sort_by (string, optional): Sort by relevance, lastUpdatedDate, or submittedDate.
• sort_order (string, optional): Sort order ascending or descending.

Example Response:

{
  "feed_title": "arXiv Query: search_query=all:machine+learning",
  "total_results": 150000,
  "start_index": 0,
  "items_per_page": 10,
  "papers": [
    {
      "id": "http://arxiv.org/abs/2104.13478",
      "arxiv_id": "2104.13478",
      "title": "Advanced Machine Learning Techniques",
      "summary": "This paper discusses advanced machine learning techniques...",
      "authors": ["John Smith", "Jane Doe"],
      "published": "2021-04-28T09:00:00Z",
      "updated": "2021-04-28T09:00:00Z",
      "categories": ["cs.LG", "cs.AI"],
      "links": [
        {
          "href": "http://arxiv.org/abs/2104.13478",
          "rel": "alternate",
          "type": "text/html"
        }
      ]
    }
  ]
}

get_paper

Get detailed information about a specific paper by its arXiv ID.

Parameters:

• paper_id (string, required): arXiv paper ID (e.g., 2104.13478 or cs/0001001).

Returns: Same structured format as search_papers but for a single paper.

search_by_category

Search for papers in a specific arXiv category with pagination and sorting options.

Parameters:

• category (string, required): arXiv category (e.g., cs.AI, physics.optics).
• start (number, optional): Starting index for pagination (0 - based).
• max_results (number, optional): Maximum number of results to return (max 2000).
• sort_by (string, optional): Sort by relevance, lastUpdatedDate, or submittedDate.
• sort_order (string, optional): Sort order ascending or descending.

get_paper_content

Download and extract the full - text content from a paper's PDF.

Parameters:

• paper_id (string, required): arXiv paper ID (e.g., 2104.13478).

Features:

• Downloads PDFs from arXiv's servers.
• Caches PDFs locally to avoid redundant downloads.
• Extracts and cleans text content using pdf - parse.
• Handles network errors and parsing issues gracefully.
• Returns plain text content suitable for analysis.

Returns: Plain text content of the paper.

📚 Documentation

Common arXiv Categories

• cs.AI - Artificial Intelligence
• cs.LG - Machine Learning
• cs.CL - Computation and Language
• cs.CV - Computer Vision and Pattern Recognition
• physics.optics - Optics
• math.CO - Combinatorics
• stat.ML - Machine Learning (Statistics)

For a complete list, see arXiv Subject Classifications.

Development

Running Tests

npm test

Build

npm run build

Watch Mode (for development)

npm run test:watch

API Reference

This server uses the official arXiv API. For more information:

• arXiv API Basics
• arXiv API User Manual

Contributing

Please read CONTRIBUTING.md for details on our code of conduct and the process for submitting pull requests.

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

Changelog

v0.1.0 (Initial Release)

• Basic arXiv API integration
• Search papers by multiple criteria
• Get individual paper details
• Category - based search
• PDF content extraction with caching
• Structured JSON response parsing
• MCP protocol implementation