Deep Research
An MCP (Model Context Protocol) server that enables comprehensive research capabilities for Claude and other MCP-compatible AI assistants. This server integrates web and academic search functionality, allowing AI models to access current information from multiple sources, follow relevant links, and provide well-structured research results.
Overview
Claude Deep Research is a powerful research tool that extends the capabilities of LLMs by providing:
- Web search integration through DuckDuckGo
- Academic research access through Semantic Scholar
- Content extraction from web pages
- Comprehensive analysis with structured formatting
- Visualization guidance for data representation
The server follows MCP design principles to provide a seamless integration with Claude and other AI assistants.
Features
- Unified Research Tool: Single interface for web and academic information
- Multi-Source Integration: Combines information from various sources into cohesive research
- Content Extraction: Pulls relevant information from web pages
- Academic Source Discovery: Finds scholarly articles related to your topic
- Smart Formatting: Properly formats research with citations
- Visual Framework: Provides guidance for creating effective data visualizations
- Structured Analysis: Organizes research using academic methodologies
Installation
Prerequisites
- Python 3.8 or higher
- pip or uv package manager
Quick Install
# Using pip
pip install mcp httpx beautifulsoup4
# Clone the repository
git clone https://github.com/yourusername/claude-deep-research.git
Configuration
The server works out of the box with default settings, but you can modify the following parameters in deep_research.py for customization:
# Configuration
USER_AGENT = "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36"
MAX_CONTENT_SIZE = 8000 # Maximum characters in the final response
MAX_RESULTS = 3 # Maximum number of results to process
Usage
Running the Server
Modify your Claude desktop config and restart Claude. On a Mac this is at ~/Library/Application Support/Claude
"search-scholar": {
"command": "<Path to Python>/python",
"args": [
"<Path to deep research>/deep_research.py"
]
}
Using with Claude Desktop
Once installed, you can access the server in Claude Desktop:
- Tool Access: Use the
deep_research
tool directly in conversation
Research Tool
The main deep_research
tool accepts the following parameters:
query
(required): The research question or topicsources
(optional): Which sources to use: "web", "academic", or "both" (default)num_results
(optional): Number of sources to examine (default 2, max 3)
Example prompts:
Can you research the latest developments in quantum computing?
I need comprehensive information about climate change mitigation strategies. Use the deep_research tool to help me.
Research the history and cultural significance of origami using academic sources.
Research Prompt
The server includes a structured research prompt that guides Claude through a comprehensive research process:
- Initial Exploration: Gathers information from multiple sources
- Preliminary Synthesis: Organizes findings with visualization
- Follow-up Research: Identifies and explores knowledge gaps
- Comprehensive Analysis: Integrates all information with visual elements
- Proper Citations: Formats references using APA style
Troubleshooting
Common Issues
- Server Connection Failures: Ensure you're using the correct path to the server file.
- Search Errors: Some searches may time out or return limited results. Try a more specific query.
- Web Access Issues: The server requires internet access to function properly.
- Content Formatting: Very large responses may be truncated to fit within size limits.
Logs
The server outputs logs to stderr that can help diagnose issues:
# View logs when running directly
python deep_research.py 2> server.log
# View logs from Claude Desktop (macOS/Linux)
tail -f ~/Library/Logs/Claude/mcp-server-deepresearch.log
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
Acknowledgments
- Built on the Model Context Protocol
- Uses DuckDuckGo for web search
- Uses Semantic Scholar for academic research
- Inspired by Anthropic's Claude
Made with ❤️ for extending AI capabilities through MCP