MCP Server Deep Research

Communauté Recherche et web

Autonomous deep research with structured query elaboration and concise reporting.

Que pouvez-vous faire avec MCP Server Deep Research ?

  • Question Elaboration
  • Subquestion Generation
  • Web Search Integration
  • Content Analysis
  • Report Generation

Installation

Les étapes d'installation sont dans la documentation ci-dessous. Documentation

Documentation

Tirée du README du projet sur GitHub, actualisée chaque semaine. Les liens ouvrent GitHub.

Sommaire
  1. MCP Server for Deep Research
  2. 🚀 Try it Out
  3. Features
  4. 📦 Components
  5. ⚙️ Modifying the Server
  6. 🛠️ Development
  7. 🤝 Contributing
  8. 📜 License

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

) Youtube: https://youtu.be/_a7sfo5yxoI

  1. Download Claude Desktop
  2. Install and Set Up
    • On macOS, run the following command in your terminal: bash 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.

Questions fréquentes

Qu'est-ce que MCP Server Deep Research ?

Autonomous deep research with structured query elaboration and concise reporting.

Comment installer MCP Server Deep Research ?

Suivez les étapes d'installation de sa documentation, affichée sur cette page et dans son dépôt.

MCP Server Deep Research est-il open source ?

Oui. Son code est sur GitHub sous licence MIT.

Qui maintient MCP Server Deep Research ?

Il est publié par reading-plus-ai. AI.tn le référence sans le maintenir ni le recommander.

Issu des listes communautaires awesome-mcp-servers et du dépôt GitHub du projet. Être listé n'est pas une recommandation : vérifiez le code et les permissions d'un serveur avant de lui donner accès à vos données.