MCP Deep Web Research Server (v0.3.0)

A Model Context Protocol (MCP) server for advanced web research.

Latest Changes
- Added visit_page tool for direct webpage content extraction
- Optimized performance to work within MCP timeout limits
- Reduced default maxDepth and maxBranching parameters
- Improved page loading efficiency
- Added timeout checks throughout the process
- Enhanced error handling for timeouts
This project is a fork of mcp-webresearch by mzxrai, enhanced with additional features for deep web research capabilities. We're grateful to the original creators for their foundational work.
Bring real-time info into Claude with intelligent search queuing, enhanced content extraction, and deep research capabilities.
Features
Prerequisites
Installation
Global Installation (Recommended)
# Install globally using npm
npm install -g mcp-deepwebresearch
# Or using yarn
yarn global add mcp-deepwebresearch
# Or using pnpm
pnpm add -g mcp-deepwebresearch
Local Project Installation
# Using npm
npm install mcp-deepwebresearch
# Using yarn
yarn add mcp-deepwebresearch
# Using pnpm
pnpm add mcp-deepwebresearch
Claude Desktop Integration
After installing the package, add this entry to your claude_desktop_config.json
:
Windows
{
"mcpServers": {
"deepwebresearch": {
"command": "mcp-deepwebresearch",
"args": []
}
}
}
Location: %APPDATA%\Claude\claude_desktop_config.json
macOS
{
"mcpServers": {
"deepwebresearch": {
"command": "mcp-deepwebresearch",
"args": []
}
}
}
Location: ~/Library/Application Support/Claude/claude_desktop_config.json
This config allows Claude Desktop to automatically start the web research MCP server when needed.
First-time Setup
After installation, run this command to install required browser dependencies:
npx playwright install chromium
Usage
Simply start a chat with Claude and send a prompt that would benefit from web research. If you'd like a prebuilt prompt customized for deeper web research, you can use the agentic-research
prompt that we provide through this package. Access that prompt in Claude Desktop by clicking the Paperclip icon in the chat input and then selecting Choose an integration
→ deepwebresearch
→ agentic-research
.
Tools
deep_research
* Performs comprehensive research with content analysis
* Arguments:
{
topic: string;
maxDepth?: number; // default: 2
maxBranching?: number; // default: 3
timeout?: number; // default: 55000 (55 seconds)
minRelevanceScore?: number; // default: 0.7
}
* Returns:
{
findings: {
mainTopics: Array<{name: string, importance: number}>;
keyInsights: Array<{text: string, confidence: number}>;
sources: Array<{url: string, credibilityScore: number}>;
};
progress: {
completedSteps: number;
totalSteps: number;
processedUrls: number;
};
timing: {
started: string;
completed?: string;
duration?: number;
operations?: {
parallelSearch?: number;
deduplication?: number;
topResultsProcessing?: number;
remainingResultsProcessing?: number;
total?: number;
};
};
}
parallel_search
* Performs multiple Google searches in parallel with intelligent queuing
* Arguments: `{ queries: string[], maxParallel?: number }`
* Note: maxParallel is limited to 5 to ensure reliable performance
visit_page
* Visit a webpage and extract its content
* Arguments: `{ url: string }`
* Returns:
{
url: string;
title: string;
content: string; // Markdown formatted content
}
Prompts
agentic-research
A guided research prompt that helps Claude conduct thorough web research. The prompt instructs Claude to:
- Start with broad searches to understand the topic landscape
- Prioritize high-quality, authoritative sources
- Iteratively refine the research direction based on findings
- Keep you informed and let you guide the research interactively
- Always cite sources with URLs
Configuration Options
The server can be configured through environment variables:
MAX_PARALLEL_SEARCHES
: Maximum number of concurrent searches (default: 5)
SEARCH_DELAY_MS
: Delay between searches in milliseconds (default: 200)
MAX_RETRIES
: Number of retry attempts for failed requests (default: 3)
TIMEOUT_MS
: Request timeout in milliseconds (default: 55000)
LOG_LEVEL
: Logging level (default: 'info')
Error Handling
Common Issues
- Rate Limiting
* Symptom: "Too many requests" error
* Solution: Increase `SEARCH_DELAY_MS` or decrease `MAX_PARALLEL_SEARCHES`
- Network Timeouts
* Symptom: "Request timed out" error
* Solution: Ensure requests complete within the 60-second MCP timeout
- Browser Issues
* Symptom: "Browser failed to launch" error
* Solution: Ensure Playwright is properly installed (`npx playwright install`)
Debugging
This is beta software. If you run into issues:
Check Claude Desktop's MCP logs:
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
Setup
# Install dependencies
pnpm install
# Build the project
pnpm build
# Watch for changes
pnpm watch
# Run in development mode
pnpm dev
Testing
# Run all tests
pnpm test
# Run tests in watch mode
pnpm test:watch
# Run tests with coverage
pnpm test:coverage
Code Quality
# Run linter
pnpm lint
# Fix linting issues
pnpm lint:fix
# Type check
pnpm type-check
Contributing
- Fork the repository
- Create your feature branch (
git checkout -b feature/amazing-feature
)
- Commit your changes (
git commit -m 'Add some amazing feature'
)
- Push to the branch (
git push origin feature/amazing-feature
)
- Open a Pull Request
Coding Standards
- Follow TypeScript best practices
- Maintain test coverage above 80%
- Document new features and APIs
- Update CHANGELOG.md for significant changes
- Follow semantic versioning
Performance Considerations
- Use batch operations where possible
- Implement proper error handling and retries
- Consider memory usage with large datasets
- Cache results when appropriate
- Use streaming for large content
Requirements
- Node.js >= 18
- Playwright (automatically installed as a dependency)
Verified Platforms
License
MIT
Credits
This project builds upon the excellent work of mcp-webresearch by mzxrai. The original codebase provided the foundation for our enhanced features and capabilities.
Author
qpd-v