McpDeepResearch
БесплатноНе проверенAn MCP server that enables academic research by searching Google Scholar, fetching paper content, and converting web pages to clean Markdown.
Описание
An MCP server that enables academic research by searching Google Scholar, fetching paper content, and converting web pages to clean Markdown.
README
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!
Установка McpDeepResearch
У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.
▸ github.com/Pb-207/mcp-deep-researchFAQ
McpDeepResearch MCP бесплатный?
Да, McpDeepResearch MCP бесплатный — установка в пару кликов через Unyly без оплаты.
Нужен ли API-ключ для McpDeepResearch?
Нет, McpDeepResearch работает без API-ключей и переменных окружения.
McpDeepResearch — hosted или self-hosted?
Self-hosted: сервер запускается локально на твоей машине командой из раздела установки.
Как установить McpDeepResearch в Claude Desktop, Claude Code или Cursor?
Открой McpDeepResearch на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.
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