MCP for Research：如何將 AI 連接到學術研究工具
Original: MCP for Research: How to Connect AI to Research Tools
As the use of AI in academic research becomes increasingly widespread, enabling large language models (LLMs) to access the latest…
Hugging Face 發表最新指南，展示如何利用 Model Context Protocol (MCP) 將 AI 模型與學術研究工具無縫串接。文章介紹了如何建立 MCP 伺服器來連接 arXiv、Semantic Scholar 及 Zotero 等文獻資料庫，讓 AI 能夠直接檢索、閱讀並整理最新學術論文。這項技術不僅能大幅降低 AI 的幻覺，還能自動化文獻回顧與資料分析流程，是科研人員與開發者構建智慧學術助理的實用指南。
As the use of AI in academic research becomes increasingly widespread, enabling large language models (LLMs) to access the latest scientific literature in real time and with accuracy has emerged as a significant challenge. Hugging Face recently published a guide detailing how to address this problem using Anthropic's open standard, the Model Context Protocol (MCP). MCP allows developers to establish standardized bidirectional channels that securely connect AI models to external data sources and tools. In a research context, this means AI is no longer limited to static training data — it can directly call academic APIs to perform real-time literature retrieval and analysis.
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