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.

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:

Install Package:

bash uv add paper-search-mcp

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

Setup Environment:

```bash # 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 ```

Install Dependencies:

```bash # 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:

Fork the Repository: Click "Fork" on GitHub.
Clone and Set Up:

bash git clone https://github.com/yourusername/paper-search-mcp.git cd paper-search-mcp pip install -e ".[dev]" # Install dev dependencies (if added to pyproject.toml)