MCP Server Deep Research

Community Search and web

Autonomous deep research with structured query elaboration and concise reporting.

What can you do with MCP Server Deep Research?

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

Install

The installation steps are in the documentation below. Documentation

Documentation

From the project's README on GitHub, refreshed weekly. Links open on GitHub.

Contents
  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.

Frequently asked questions

What is MCP Server Deep Research?

Autonomous deep research with structured query elaboration and concise reporting.

How do I install MCP Server Deep Research?

Follow the installation steps in its documentation, shown on this page and in its repository.

Is MCP Server Deep Research open source?

Yes. Its code is on GitHub under the MIT license.

Who maintains MCP Server Deep Research?

It is published by reading-plus-ai. AI.tn lists it but does not maintain or endorse it.

From the community awesome-mcp-servers lists and the project's GitHub repository. Listing is not an endorsement: review a server's code and permissions before giving it access to your data.