MCP DEEPwebresearch

The MCP Deep Web Research Server is an advanced web research tool based on Node.js, providing intelligent search queues, enhanced content extraction, and in-depth research capabilities, and can be integrated into the Claude desktop application.

Research and data Search tools #Web Research #Intelligent Search #Content Extraction #Claude Integration .TypeScript

rating : 2.5 points

downloads : 6.7K

update time : 2025-04-29

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What is the MCP Deep Web Research Server?

The MCP Deep Web Research Server is a powerful tool designed for research tasks that require real-time Internet information. It helps you quickly obtain the information you need through intelligent search queues, enhanced content extraction, and in-depth web research capabilities.

How to use the MCP Deep Web Research Server?

Simply start a conversation and send the topic you need to research. The server will automatically perform a comprehensive web search and provide detailed analysis results.

Applicable Scenarios

Suitable for researchers, students, and enterprise users who need to quickly obtain high-quality information. For example, in fields such as market research, academic research, and news reporting.

Main Features

Intelligent Search Queue System

Supports batch search operations, has a rate-limiting function, can manage task progress, and automatically retry failed requests.

Enhanced Content Extraction

Scores relevant content through the TF-IDF algorithm, supports keyword proximity analysis and structured data extraction.

Google Search Integration

Directly integrates the Google Search API to improve search efficiency.

Deep Research Mode

Supports multi-layer search and branch expansion, suitable for complex topic research.

Advantages

Supports intelligent search queues to improve efficiency

Powerful content extraction ability to ensure accurate information

Integrates Google Search for wide coverage

Supports multiple languages to meet the needs of international users

Limitations

Requires a stable network connection

Some advanced functions may be affected by API limitations

The processing speed may be slow for very large data sets

How to Use

Install the Server

Install the server globally: Run `npm install -g mcp-deepwebresearch`.

Configure the Claude Desktop Application

Add the server address to the Claude desktop configuration file.

Start Research

Start a Claude conversation, enter your research topic, and the server will automatically perform the search and return the results.

Usage Examples

Case 1: Historical Development of Artificial Intelligence

Research the development process of artificial intelligence and obtain key findings and authoritative sources.

Case 2: Latest Technological Trends

Explore current popular technological trends and obtain industry dynamics.

Frequently Asked Questions

How to solve the network timeout problem?

Does it support multi-language search?

Related Resources

Official Documentation

Detailed server usage guide.

GitHub Code Repository

Open-source project homepage.

Demo Video

Watch a demonstration of the server's actual operation.

🚀 MCP Depth Project

MCP Depth is a project that uses Playwright for browser automation. It provides a set of tools and scripts to streamline development, testing, and deployment processes.

🚀 Quick Start

MCP Depth is a project designed for browser automation using Playwright. Below is a detailed guide to help you get started.

✨ Features

Automate browser operations with Playwright.
Comprehensive testing and code quality checking tools.
Configurable through environment variables.

📦 Installation

Install Dependencies

pnpm install

Build the Project

pnpm build

Monitor File Changes

pnpm watch

Run in Development Mode

pnpm dev

💻 Usage Examples

Testing Instructions

Run All Tests

pnpm test

Run Tests in Watch Mode

pnpm test:watch

Run Tests with Coverage

pnpm test:coverage

Code Quality Checks

Perform Code Checks

pnpm lint

Automatically Fix Code Issues

pnpm lint:fix

Perform Type Checks

pnpm type-check

📚 Documentation

Configuration Options

The project can be configured via environment variables:

Property	Details
`MAX_PARALLEL_SEARCHES`	Maximum number of parallel searches (default is 5).
`SEARCH_DELAY_MS`	Delay between each search (in milliseconds, default is 200).
`MAX_RETRIES`	Number of retries for failed requests (default is 3).
`TIMEOUT_MS`	Request timeout (in milliseconds, default is 55000).
`LOG_LEVEL`	Log level (default is 'info').

Error Handling

Common Issues

Rate Limiting
- Symptom: "Too many requests" error.
- Solution: Increase SEARCH_DELAY_MS or decrease MAX_PARALLEL_SEARCHES.
Network Timeout
- Symptom: "Request timed out" error.
- Solution: Ensure requests are completed within the 60 - second MCP timeout limit.
Browser Issues
- Symptom: "Browser failed to launch" error.
- Solution: Ensure Playwright is correctly installed (by running npx playwright install).

Debugging Methods

Check the MCP logs of Claude Desktop:

# On macOS
tail -n 20 -f ~/Library/Logs/Claude/mcp*.log

# On Windows
Get-Content -Path "$env:APPDATA\Claude\logs\mcp*.log" -Tail 20 -Wait

Enable debug logging:
```
export LOG_LEVEL=debug
```

Development Guide

Project Setup

# Install dependencies
pnpm install

# Build the project
pnpm build

# Monitor file changes
pnpm watch

# Run in development mode
pnpm dev

Testing Guide

# Run all tests
pnpm test

# Run tests in watch mode
pnpm test:watch

# Run tests with coverage
pnpm test:coverage

Code Quality

# Perform code checks
pnpm lint

# Automatically fix code issues
pnpm lint:fix

# Perform type checks
pnpm type-check

Contribution Guidelines

Code Style
- Use the default JavaScript/TypeScript color scheme in VSCode.
- Do not add auto - generated copyright statements to files.
Commit Specification
- Please refer to the CONTRIBUTING.md file in the project repository.