McpDeepResearch
Allows searching Google Scholar for academic papers with optional year filtering and date sorting, and fetching paper content from URLs.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@McpDeepResearchFind recent papers on diffusion models from 2023"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
🔍 McpDeepResearch
An MCP (Model-Context-Protocol) Server for Deep Academic Research
一个用于深度学术研究的 MCP 服务器
English
McpDeepResearch is a lightweight but powerful MCP (Model-Context-Protocol) server that helps you quickly discover, retrieve, and read academic papers from the web using the familiar Google Scholar interface.
✨ Features
search_scholar_papers – Google Scholar search with optional year-filter & date-sort
fetch_md – Convert any public web page to clean Markdown
fetch_paper – Auto-detect the paper content (title, abstract, body, references) and strip the rest
🛠️ Prerequisites
Python ≥ 3.10
Google Chrome/Chromium (for headless fetching via Chrome DevTools Protocol)
Environment variables
export CDP_ENDPOINT="http://localhost:9222" # Chrome debugging port export GOOGLE_PROXY="http://proxy:port" # (optional) HTTP(S) proxy
⚙️ Quick Start
Install via pip
pip install(Optional) Manually launch Chrome if it isn’t already running
The server will automatically launch a Chrome instance; if not successfully launched, you can launch it manually with:google-chrome --remote-debugging-port=9222 --user-data-dir=/tmp/chrome-profile & ``Run the MCP server
# Launch with SSE mcp-deep-research --transport sse --port 8000 # Launch with STDIO mcp-deep-research --transport stdioThe server exposes 3 read-only tools to any MCP-capable client.
🧑🎓 Example Workflow in a Chat-UI
Search
“Find recent papers on diffusion models after 2022.”
→search_scholar_papers("diffusion models", year=2022, sort_bd=True)Fetch
Pick an interesting PDF link from the results and callfetch_paper("https://arxiv.org/abs/2304.12345")Read
The cleaned Markdown (title, abstract, full text) appears directly in the chat.
🔒 Security
100 % read-only; no writes, no uploads, no local file access.
All traffic respects the original site’s robots.txt.
Proxies can be configured to stay within institutional or regional firewalls.
🤝 Contributing
PRs are welcome!
简体中文
McpDeepResearch 是一个轻量级、但功能完备的 MCP(Model-Context-Protocol)服务器,帮助你在 Google Scholar 上快速发现、抓取并阅读学术文献。
✨ 功能一览
search_scholar_papers – 使用关键词在 Google Scholar 中搜索,可过滤年份 / 按日期排序
fetch_md – 将任意公开网页渲染为整洁的 Markdown
fetch_paper – 智能提取网页中的论文主体,去除广告、导航条等噪声
🛠️ 前置条件
Python ≥ 3.10
Google Chrome / Chromium(通过 CDP 进行无头抓取)
环境变量
export CDP_ENDPOINT="http://localhost:9222" # Chrome 调试端口 export GOOGLE_PROXY="http://proxy:port" # 可选:HTTP(S) 代理
⚙️ 快速开始
通过 pip 安装
pip install(可选)如果 Chrome 尚未启动可手动启动
服务器启动时会自动运行 Chrome 实例。若未成功启动,可手动启动:google-chrome --remote-debugging-port=9222 --user-data-dir=/tmp/chrome-profile &启动 MCP 服务器
# 以 SSE 启动 mcp-deep-research --transport sse --port 8000 # 以 STDIO 启动 mcp-deep-research --transport stdio服务器会对外暴露 3 个只读工具。
🧑🎓 对话界面中的典型工作流
搜索
“找 2022 年之后关于扩散模型的论文。”
→search_scholar_papers("diffusion models", year=2022, sort_bd=True)抓取
从结果中挑选一篇 PDF 链接,调用fetch_paper("https://arxiv.org/abs/2304.12345")阅读
清洗后的 Markdown(含标题、摘要、全文)直接展示在聊天窗口。
🔒 安全性
完全只读,不修改、不上传、不写入本地文件。
所有请求均尊重目标站点的 robots.txt。
可配置代理以符合校园网或公司网络的安全策略。
🤝 如何贡献
欢迎提 PR!
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