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Built with ❤️ by Krishna Goyal

    Mcp Server Deep Research

    Your personal Research Assistant, turning research questions into comprehensive, well-cited reports. Built for the Model Context Protocol to enhance AI capabili

    183 stars
    Python
    Updated Oct 15, 2025

    Table of Contents

    • 🚀 Try it Out
    • Features
    • 📦 Components
    • Prompts
    • ⚙️ Modifying the Server
    • Claude Desktop Configurations
    • Development (Unpublished Servers)
    • Published Servers
    • 🛠️ Development
    • Building and Publishing
    • 🤝 Contributing
    • 📜 License

    Table of Contents

    • 🚀 Try it Out
    • Features
    • 📦 Components
    • Prompts
    • ⚙️ Modifying the Server
    • Claude Desktop Configurations
    • Development (Unpublished Servers)
    • Published Servers
    • 🛠️ Development
    • Building and Publishing
    • 🤝 Contributing
    • 📜 License

    Documentation

    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

    • Get it here

    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)

    json
    "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

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

    🛠️ Development

    Building and Publishing

    1. Sync Dependencies

    bash
    uv sync

    2. Build Distributions

    bash
    uv build

    Generates source and wheel distributions in the dist/ directory.

    3. Publish to PyPI

    bash
    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.

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