A MCP server for searching and downloading academic papers from multiple sources.
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# 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.    [](https://smithery.ai/server/@openags/paper-search-mcp) --- ## Table of Contents - [Overview](#overview) - [Features](#features) - [Installation](#installation) - [Quick Start](#quick-start) - [Install Package](#install-package) - [Configure Claude Desktop](#configure-claude-desktop) - [For Development](#for-development) - [Setup Environment](#setup-environment) - [Install Dependencies](#install-dependencies) - [Contributing](#contributing) - [Demo](#demo) - [License](#license) - [TODO](#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. --- ## In…
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