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McpDeepResearch

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An MCP server that enables academic research by searching Google Scholar, fetching paper content, and converting web pages to clean Markdown.

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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 | 简体中文


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

  1. Install via pip

    pip install 
    
  2. (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 &
    ``
    
  3. Run the MCP server

    # Launch with SSE
    mcp-deep-research --transport sse --port 8000
    # Launch with STDIO
    mcp-deep-research --transport stdio
    

    The server exposes 3 read-only tools to any MCP-capable client.

🧑‍🎓 Example Workflow in a Chat-UI

  1. Search
    “Find recent papers on diffusion models after 2022.”
    search_scholar_papers("diffusion models", year=2022, sort_bd=True)

  2. Fetch
    Pick an interesting PDF link from the results and call
    fetch_paper("https://arxiv.org/abs/2304.12345")

  3. 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

  1. 通过 pip 安装

    pip install 
    
  2. (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 &
    
  3. 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

  1. 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)

  2. 抓取
    从结果中挑选一篇 PDF 链接,调用
    fetch_paper("https://arxiv.org/abs/2304.12345")

  3. 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!


from github.com/Pb-207/mcp-deep-research

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-research

FAQ

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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