Deep Research MCP Server

🚀 Deep Research: Intelligent Search Engine and Analysis Tool

Deep Research is a comprehensive research platform integrating web crawlers, AI model calls, and data analysis. It aims to help users efficiently acquire, process, and analyze Internet information, suitable for various scenarios such as academic research, business intelligence collection, and news reporting.

✨ Features

1. Intelligent Search and Crawling Engine

• Deep Web Crawling: Supports multi - threaded concurrent crawling, scalable to thousands of requests per second.
• AI - Driven Content Recognition: Utilizes models like Gemini to automatically recognize and classify web page content.
• Structured Data Extraction: Extracts key information from unstructured text to form a standardized data format.

2. AI Analysis Engine

• Multi - Language Support: Supports text processing in multiple languages, including English and Chinese.
• Semantic Understanding and Analysis: Conducts in - depth semantic analysis based on the Gemini model, generating summaries and extracting keywords.
• Association Analysis: Discovers the relationship network between different data points through graph computing technology.

3. Data Storage and Management

• Distributed Storage: Employs a scalable distributed file system, supporting PB - level data storage.
• Metadata Management: Automatically records information such as crawling time and source URL for subsequent tracing and verification.
• Version Control: Tracks different versions of research results to ensure data traceability.

📚 Documentation

Supported Search Engines

• Google Custom Search API: Provides powerful search capabilities and related web page extraction functions.
• Bing Web Search API: An efficient web search service provided by Microsoft.
• DuckDuckGo API: A privacy - first search solution.

AI Model Integration

• Gemini Series: Includes multiple versions to support different processing capacity requirements.
• Claude & ChatGPT: Enables multi - modal content generation and analysis through API calls.
• Custom Model Support: Allows users to load and use their own AI models.

📦 Use Cases

1. Academic Research

• Supports research activities such as literature reviews and data collection, enhancing academic productivity.

2. Business Intelligence

• Helps enterprises conduct market analysis, competitor analysis, and trend prediction.

3. News and Media

• Provides journalists with fast information retrieval and in - depth content mining functions.

🔧 Technical Details

Modular Architecture

• Crawling Module: Responsible for obtaining web page data.
• Processing Module: Cleans and structures the obtained data.
• Analysis Module: Conducts in - depth analysis of data using AI models to extract useful information.
• Storage Module: Provides a persistent storage solution.

Concurrency and Performance Optimization

• Multi - Threaded/Process Model: Supports high - concurrency operations to improve processing efficiency.
• Asynchronous IO: Adopts a non - blocking I/O model to improve the response speed of network requests.

📦 Installation

Environment Requirements

• Node.js Environment: Version 22.x is recommended.
• API Keys:
  • Firecurl API Key
  • Gemini API Key
  • Credentials for other third - party services

Technical Dependencies

• Network Request Libraries: Such as axios, needle
• Concurrency Processing Libraries: Such as puppeteer, scrapy
• AI Frameworks: Such as tensorflow.js, huggingface.js

💻 Usage Examples

As an MCP Tool

npm install deep-research-cli -g
deep-research --query "Artificial Intelligence" --mode research

Stand - Alone CLI Usage

const DeepResearch = require('deep-research');
const dr = new DeepResearch({
  apiKey: 'your_api_key',
  verbose: true
});
dr.search('Quantum Computing')
  .then(results => console.log(results))
  .catch(err => console.error(err));

🆕 Recent Improvements

v0.2.0 (2023 - 10 - 15)

Feature Enhancements

• Intelligent Content Recognition: Newly added multi - language support and semantic understanding functions.
• Result Optimization
  • Higher search accuracy
  • Support for more data formats (e.g., JSON, CSV)
• Performance Improvement
  • 30% increase in network request speed
  • 20% reduction in memory usage

New Features

• Content Verification: Automatically detects and filters low - quality information.
• Result Visualization: Supports generating charts and reports.
• Logging System: Records operation history in detail for easy troubleshooting.

📅 Future Plans

Short - Term Goals (Next 1 Month)

• Optimize the call performance of the Gemini model.
• Support more AI models.
• Improve the error handling mechanism.

Medium - Term Goals (Next 3 Months)

• Implement automatic data cleaning functions.
• Develop advanced analysis tools.
• Enhance data visualization capabilities.

📞 Contact Us

Join our developer community and participate in project discussions: [GitHub Link]

Follow our blog for the latest updates: [Official Blog Link]