Paper Search MCP

A Model Context Protocol (MCP) server for searching and downloading academic papers from multiple sources, including arXiv, PubMed, bioRxiv, and Sci-Hub (optional). Designed for seamless integration with large language models like Claude Desktop.

Table of Contents

• Overview
• Features
• Installation
  • Quick Start
    • Install Package
    • Configure Claude Desktop
  • For Development
    • Setup Environment
    • Install Dependencies
• Contributing
• Demo
• License
• TODO

Overview

paper-search-mcp is a Python-based MCP server that enables users to search and download academic papers from various platforms. It provides tools for searching papers (e.g., search_arxiv) and downloading PDFs (e.g., download_arxiv), making it ideal for researchers and AI-driven workflows. Built with the MCP Python SDK, it integrates seamlessly with LLM clients like Claude Desktop.

Features

• Multi-Source Support: Search and download papers from arXiv, PubMed, bioRxiv, medRxiv, Google Scholar, IACR ePrint Archive, Semantic Scholar.
• Standardized Output: Papers are returned in a consistent dictionary format via the Paper class.
• Asynchronous Tools: Efficiently handles network requests using httpx.
• MCP Integration: Compatible with MCP clients for LLM context enhancement.
• Extensible Design: Easily add new academic platforms by extending the academic_platforms module.

Installation

paper-search-mcp can be installed using uv or pip. Below are two approaches: a quick start for immediate use and a detailed setup for development.

Installing via Smithery

To install paper-search-mcp for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @openags/paper-search-mcp --client claude

Quick Start

For users who want to quickly run the server:

1. Install Package:

   uv add paper-search-mcp
   

2. Configure Claude Desktop: Add this configuration to ~/Library/Application Support/Claude/claude_desktop_config.json (Mac) or %APPDATA%\Claude\claude_desktop_config.json (Windows):

   {
     "mcpServers": {
       "paper_search_server": {
         "command": "uv",
         "args": [
           "run",
           "--directory",
           "/path/to/your/paper-search-mcp",
           "-m",
           "paper_search_mcp.server"
         ],
         "env": {
           "SEMANTIC_SCHOLAR_API_KEY": "" // Optional: For enhanced Semantic Scholar features
         }
       }
     }
   }
   

   Note: Replace /path/to/your/paper-search-mcp with your actual installation path.

For Development

For developers who want to modify the code or contribute:

1. Setup Environment:

   # Install uv if not installed
   curl -LsSf https://astral.sh/uv/install.sh | sh
   
   # Clone repository
   git clone https://github.com/openags/paper-search-mcp.git
   cd paper-search-mcp
   
   # Create and activate virtual environment
   uv venv
   source .venv/bin/activate  # On Windows: .venv\Scripts\activate
   

2. Install Dependencies:

   # Install project in editable mode
   uv add -e .
   
   # Add development dependencies (optional)
   uv add pytest flake8
   

Contributing

We welcome contributions! Here's how to get started:

1. Fork the Repository: Click "Fork" on GitHub.

2. **Cl

... View full README on GitHub