Paper Search

概要

Paper Search is a Python-based Model Context Protocol (MCP) server that enables users to efficiently search and download academic papers from a wide array of platforms such as arXiv, PubMed, bioRxiv, Google Scholar, and Semantic Scholar. It provides standardized tools for both searching and fetching PDF documents, making it an indispensable asset for researchers and AI-driven workflows. Built with the MCP Python SDK, Paper Search seamlessly integrates with large language model clients like Claude Desktop to enhance their contextual understanding and research capabilities.

主な機能

• Provides standardized `search` and `fetch` tools compatible with OpenAI Deep Research and ChatGPT connectors.
• Multi-source paper search and download from platforms like arXiv, PubMed, bioRxiv, Google Scholar, and Semantic Scholar.
• Extensible design allowing for easy addition of new academic platforms and sources.
• Seamless integration with LLM clients through Model Context Protocol (MCP) for context enhancement.
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• Outputs retrieved paper information in a consistent dictionary format via a `Paper` class.

ユースケース

• Integrating paper search and retrieval capabilities into AI-driven research and analysis workflows.
• Enhancing large language models (LLMs) with real-time access to current and historical research literature.
• Automating the discovery and download of academic papers for researchers.