paper-search-mcp-openai

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.

[](https://smithery.ai/server/@openags/paper-search-mcp)

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

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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.

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• Multi-Source Support: Search and download papers from arXiv, PubMed, bioRxiv, medRxiv, Google Scholar, IACR ePrint Archive, Semantic Scholar.
• Deep Research Ready: Provides the standardized search and fetch tools required by OpenAI Deep Research and ChatGPT connectors.
• 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 c