MCP SiftCurated directory

深度研究用MCP服务器

by reading-plus-ai

用于深度研究和报告生成的MCP服务器。不需要明确的外部数据文件。

Education & sciencestdioCommunity

Repository-wide counts · Cached 2026-03-07

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Overview

The 深度研究用MCP服务器 MCP server is a publicly available project. Review the upstream repository for installation instructions, supported tools, compatibility, permissions, and current maintenance status.

Configuration

Configuration, transport, authentication, and runtime requirements vary by project. Open the repository before connecting and use the smallest set of credentials and permissions required.

Open the 深度研究用MCP服务器 repository to read the latest documentation.

KEEP EXPLORING

Compare source, connection, and authentication details before choosing an implementation.

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Deep Research

u14app

Community

Deep Research 使用强大的 AI 模型快速生成深入的研究报告。支持 SSE API 和 MCP 服务器。需要在 .env 文件中配置环境变量以设置服务器端的 API 密钥和相关参数。

Education & science

TorchLeet

Exorust

Community

TorchLeet provides 68 PyTorch problems from real ML/AI interviews at companies like Google, Meta, and Anthropic. It includes an AI Tutor MCP server that gives AI assistants access to problems, hints, prep plans, and learning paths with a no-spoilers teaching style.

Education & science

Zotero MCP

54yyyu

Community

用于 Zotero 的模型上下文协议（MCP）服务器，将您的 Zotero 研究库与 Claude 及其他 AI 助手连接。支持本地和 Web API 访问、PDF 注释提取以及高级搜索功能。完整本地 API 功能需要 Python 3.10 及 Zotero 7 以上版本。配置可以通过环境变量或 JSON 配置文件进行设置。

Education & science

mcp-brasil

mcp-brasil

Community

MCP Server for 70 Brazilian public data sources covering economy, legislation, transparency, judiciary, elections, environment, health, education, public security, and more. Some APIs require optional API keys configured via environment variables (e.g., TRANSPARENCIA_API_KEY, DATAJUD_API_KEY, META_ACCESS_TOKEN).

Education & science
FROM THE SOURCE

Repository README

Build-time snapshot · Retrieved 2026-10-05

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MCP Server for Deep Research

MCP Server for Deep Research is a tool designed for conducting comprehensive research on complex topics. It helps you explore questions in depth, find relevant sources, and generate structured research reports.

Your personal Research Assistant, turning research questions into comprehensive, well-cited reports.

🚀 Try it Out

Watch the demo Youtube: https://youtu.be/_a7sfo5yxoI

  1. Download Claude Desktop

  2. Install and Set Up

    • On macOS, run the following command in your terminal:
    python setup.py

  3. Start Researching

    • Select the deep-research prompt template from MCP
    • Begin your research by providing a research question

Features

The Deep Research MCP Server offers a complete research workflow:

  1. Question Elaboration

    • Expands and clarifies your research question
    • Identifies key terms and concepts
    • Defines scope and parameters

  2. Subquestion Generation

    • Creates focused subquestions that address different aspects
    • Ensures comprehensive coverage of the main topic
    • Provides structure for systematic research

  3. Web Search Integration

    • Uses Claude's built-in web search capabilities
    • Performs targeted searches for each subquestion
    • Identifies relevant and authoritative sources
    • Collects diverse perspectives on the topic

  4. Content Analysis

    • Evaluates information quality and relevance
    • Synthesizes findings from multiple sources
    • Provides proper citations for all sources

  5. Report Generation

    • Creates well-structured, comprehensive reports as artifacts
    • Properly cites all sources used
    • Presents a balanced view with evidence-based conclusions
    • Uses appropriate formatting for clarity and readability

📦 Components

Prompts

  • deep-research: Tailored for comprehensive research tasks with a structured approach

⚙️ Modifying the Server

Claude Desktop Configurations

  • macOS: ~/Library/Application\ Support/Claude/claude_desktop_config.json
  • Windows: %APPDATA%/Claude/claude_desktop_config.json

Development (Unpublished Servers)

"mcpServers": {
  "mcp-server-deep-research": {
    "command": "uv",
    "args": [
      "--directory",
      "/Users/username/repos/mcp-server-application/mcp-server-deep-research",
      "run",
      "mcp-server-deep-research"
    ]
  }
}

Published Servers

"mcpServers": {
  "mcp-server-deep-research": {
    "command": "uvx",
    "args": [
      "mcp-server-deep-research"
    ]
  }
}

🛠️ Development

Building and Publishing

  1. Sync Dependencies

    uv sync

  2. Build Distributions

    uv build

    Generates source and wheel distributions in the dist/ directory.

  3. Publish to PyPI

    uv publish

🤝 Contributing

Contributions are welcome! Whether you're fixing bugs, adding features, or improving documentation, your help makes this project better.

📜 License

This project is licensed under the MIT License. See the LICENSE file for details.