Google Research MCP Server

A powerful Model Context Protocol (MCP) server that provides AI assistants with advanced web research capabilities, including Google search integration, intelligent content extraction, and multi-source synthesis.

🚀 Features

Core Research Capabilities

Google Search Integration - Programmatic access to Google's search results with advanced filtering
Intelligent Content Extraction - Clean, structured extraction from web pages with fallback strategies
Multi-Source Synthesis - Combine information from multiple sources into coherent reports
Contextual Navigation - Smart web browsing that follows relevant links automatically
Research Workflow Automation - Complete research pipelines from query to final report

Production-Ready Features

Smart Caching - Optimized performance with configurable cache strategies
Rate Limiting - Built-in protection against API abuse
Health Monitoring - Comprehensive system health checks and metrics
Structured Logging - Production-grade logging with multiple output formats
Container Support - Docker deployment with health checks and monitoring

Enhanced Content Processing

Structure Preservation - Maintains tables, lists, and hierarchical content
Multiple Output Formats - Markdown, HTML, and plain text support
Metadata Extraction - Captures publication dates, authors, and citation information
Content Summarization - Automatic generation of content summaries
Image Context - Extracts and describes images within content

📦 Installation

Prerequisites

Node.js 18+ and npm 8+
Google Custom Search API key (Get one here)
Google Custom Search Engine ID (Create one here)

Quick Start (Unified Server)

The Google Research MCP Server now provides both search and research capabilities in a single unified server - no need to run separate instances!

Option 1: Direct Installation (No Docker Required)

Clone and Install

git clone https://github.com/your-org/google-research-mcp-server.git
cd google-research-mcp-server
npm install

Configure Environment

cp .env.example .env
# Edit .env file with your Google API credentials
nano .env  # or use your preferred editor

Validate Configuration
```
npm run validate-config
```
Build and Start
```
npm run build
npm start
```
Verify Server is Running
```
npm run health-check
```

Option 2: Docker Installation (Recommended for Production)

# 1. Clone repository
git clone https://github.com/your-org/google-research-mcp-server.git
cd google-research-mcp-server

# 2. Configure environment
cp .env.example .env
# Edit .env with your API keys

# 3. Deploy with Docker
docker-compose up -d

# 4. Verify deployment
docker-compose logs -f google-research-mcp
npm run docker:health

Option 3: Development Mode

For development with auto-rebuild:

# Terminal 1: Watch for changes and rebuild
npm run dev

# Terminal 2: Start server (after initial build)
npm start

⚙️ Configuration

Required Environment Variables

# Google API Configuration (Required)
GOOGLE_API_KEY=your_google_api_key_here
GOOGLE_SEARCH_ENGINE_ID=your_search_engine_id_here

# Server Configuration (Optional)
NODE_ENV=production
LOG_LEVEL=info

Optional Configuration

# Performance Tuning
SEARCH_CACHE_TTL_MINUTES=5        # Search result cache duration
CONTENT_CACHE_TTL_MINUTES=30      # Content extraction cache duration
MAX_CACHE_ENTRIES=100             # Maximum cache entries

# Request Limits
REQUEST_TIMEOUT_MS=30000          # Request timeout
MAX_CONTENT_SIZE_MB=50            # Maximum content size
CONCURRENT_REQUEST_LIMIT=10       # Concurrent request limit

# Rate Limiting
RATE_LIMIT_WINDOW_MS=60000        # Rate limit window
RATE_LIMIT_MAX_REQUESTS=100       # Max requests per window

Validate Configuration

npm run validate-config

🔧 Usage

MCP Client Integration

The server provides unified search and research capabilities in a single MCP server. Add to your MCP client configuration (e.g., Claude Desktop):

{
  "mcpServers": {
    "google-research": {
      "command": "node",
      "args": ["path/to/google-research-mcp-server/dist/server.js"],
      "env": {
        "GOOGLE_API_KEY": "your_api_key",
        "GOOGLE_SEARCH_ENGINE_ID": "your_search_engine_id"
      }
    }
  }
}

Alternative Configuration (with environment file):

{
  "mcpServers": {
    "google-research": {
      "command": "npm",
      "args": ["start"],
      "cwd": "path/to/google-research-mcp-server"
    }
  }
}

Note: This assumes you have a .env file configured in the project directory.

Available Tools

Search Tools

google_search - Search Google with advanced filtering options

Query: "climate change effects"
Options: site filter, date restrictions, language, result type

Content Extraction Tools

extract_webpage_content - Extract clean content from web pages
extract_multiple_webpages - Batch extract from multiple URLs
structured_content_extraction - Enhanced extraction with structure preservation
summarize_webpage - Generate webpage summaries

Research & Synthesis Tools

research_topic - Comprehensive topic research with multiple sources
synthesize_content - Combine multiple sources into coherent reports
enhanced_synthesis - Advanced synthesis with contradiction detection

Navigation Tools

contextual_navigation - Smart web browsing following relevant links

Example Usage Scenarios

Basic Research

1. Search: google_search("renewable energy trends 2024")
2. Extract: extract_webpage_content(top_result_url)
3. Analyze: Multiple sources for comprehensive view

Comprehensive Research Report

1. Research: research_topic("artificial intelligence in healthcare")
2. Synthesis: enhanced_synthesis(multiple_sources)
3. Export: Formatted report with citations

Competitive Analysis

1. Search: Multiple queries for competitor information
2. Navigate: contextual_navigation(competitor_websites)
3. Synthesize: Compare and contrast findings

🛠️ Troubleshooting

Common Issues

🔴 API Authentication Errors

Error: Missing required environment variables: GOOGLE_API_KEY

Solution:

Verify API key is correctly set in .env file
Ensure Google Custom Search API is enabled in Google Cloud Console
Check API key has proper permissions and quotas
Validate configuration: npm run validate-config

🔴 Rate Limiting Issues

Error: Rate limit exceeded for search requests

Solution:

Check your Google API quota in Google Cloud Console
Adjust rate limiting settings in environment variables
Implement request queuing for high-volume usage
Consider upgrading your Google API plan

🔴 Content Extraction Failures

Error: Failed to extract content from webpage

Solution:

Verify the target URL is accessible
Check if the website blocks automated requests
Ensure proper User-Agent headers are configured
Try different extraction methods (structured vs. standard)

🔴 Memory Issues

Warning: Memory usage high: 85%

Solution:

Reduce cache sizes in configuration
Lower concurrent request limits
Monitor content extraction sizes
Consider scaling horizontally

🔴 Docker Deployment Issues

Container health check failing

Solution:

Check container logs: docker-compose logs -f google-research-mcp
Verify environment variables are properly set
Ensure API connectivity from container
Run manual health check: npm run docker:health

🔴 Non-Docker Deployment Issues

Error: Cannot find module 'dist/server.js'

Solution:

Ensure you've built the project: npm run build
Check that dist/ directory exists and contains compiled files
Verify TypeScript compilation: npx tsc --noEmit
Clear and rebuild: rm -rf dist/ && npm run build

Error: EACCES permission denied

Solution:

Check file permissions: ls -la dist/server.js
Make executable if needed: chmod +x dist/server.js
Run with explicit node: node dist/server.js

Debug Mode

# Enable detailed logging (Non-Docker)
export LOG_LEVEL=debug
npm start

# Enable detailed logging (Docker)
docker-compose exec google-research-mcp sh -c "LOG_LEVEL=debug npm start"

# Check system health
npm run health-check

# Monitor performance (Docker)
docker-compose exec google-research-mcp npm run health-check

Non-Docker Production Deployment

For production deployment without Docker:

Using PM2 (Recommended)

# Install PM2 globally
npm install -g pm2

# Start with PM2
pm2 start dist/server.js --name "google-research-mcp"

# Monitor
pm2 status
pm2 logs google-research-mcp

# Auto-restart on system reboot
pm2 startup
pm2 save

Using systemd (Linux)

Create /etc/systemd/system/google-research-mcp.service:

[Unit]
Description=Google Research MCP Server
After=network.target

[Service]
Type=simple
User=your-user
WorkingDirectory=/path/to/google-research-mcp-server
ExecStart=/usr/bin/node dist/server.js
Restart=always
RestartSec=10
Environment=NODE_ENV=production
EnvironmentFile=/path/to/google-research-mcp-server/.env

[Install]
WantedBy=multi-user.target

Then:

sudo systemctl enable google-research-mcp
sudo systemctl start google-research-mcp
sudo systemctl status google-research-mcp

Direct Node.js (Development)

# Simple start
npm start

# With specific environment
NODE_ENV=production LOG_LEVEL=info npm start

# Background process
nohup npm start > server.log 2>&1 &

Performance Optimization

Cache Tuning

# For high-volume usage
SEARCH_CACHE_TTL_MINUTES=10
CONTENT_CACHE_TTL_MINUTES=60
MAX_CACHE_ENTRIES=200

# For memory-constrained environments
SEARCH_CACHE_TTL_MINUTES=2
CONTENT_CACHE_TTL_MINUTES=15
MAX_CACHE_ENTRIES=50

Request Optimization

# For faster responses
REQUEST_TIMEOUT_MS=15000
MAX_CONTENT_SIZE_MB=25
CONCURRENT_REQUEST_LIMIT=5

# For comprehensive extraction
REQUEST_TIMEOUT_MS=60000
MAX_CONTENT_SIZE_MB=100
CONCURRENT_REQUEST_LIMIT=15

📊 Monitoring & Health Checks

Built-in Health Monitoring

# Check overall system health
npm run health-check

# Monitor with Docker
docker-compose exec google-research-mcp npm run health-check

Health Check Response

{
  "status": "healthy",
  "timestamp": "2024-01-15T10:30:00Z",
  "environment": "production",
  "uptime": 3600000,
  "checks": {
    "googleSearch": { "status": "pass", "responseTime": 245 },
    "contentExtraction": { "status": "pass", "responseTime": 567 },
    "memory": { "status": "pass", "percentage": 45.2 }
  }
}

Monitoring Integration

Prometheus metrics available at /metrics (if enabled)
Structured logging compatible with ELK stack
Docker health checks for container orchestration

🔄 Maintenance

Regular Maintenance Tasks

# Update dependencies
npm audit
npm update

# Security audit
npm run audit:security

# Dependency analysis
npm run audit:dependencies

# Container updates
docker-compose pull
docker-compose up -d

Log Management

# View logs
docker-compose logs -f google-research-mcp

# Log rotation (configure in docker-compose.yml)
docker-compose exec google-research-mcp logrotate -f /etc/logrotate.conf

🚀 Advanced Usage

Scaling Considerations

Horizontal Scaling: Deploy multiple instances behind load balancer
Caching Strategy: Consider Redis for shared caching across instances
Rate Limiting: Implement distributed rate limiting for multi-instance deployments

Custom Configurations

Research Templates: Create custom research workflow templates
Content Filters: Implement custom content filtering rules
Export Formats: Add custom export format handlers

Integration Examples

CI/CD Pipeline: Automated research report generation
Slack Bot: Real-time research queries from team chat
Web Dashboard: Research workflow management interface

📝 Development

Development Setup

# Install dependencies
npm install

# Start in development mode
npm run dev

# Build for production
npm run build

Project Structure

src/
├── config/          # Configuration management
├── handlers/        # Tool request handlers
├── services/        # Core service implementations
├── tools/           # Tool definitions and schemas
├── types/           # TypeScript type definitions
├── utils/           # Utility functions
└── server.ts        # Main server entry point

🤝 Contributing

Fork the repository
Create a feature branch
Make your changes
Add tests if applicable
Submit a pull request

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🆘 Support

Getting Help

GitHub Issues: Report bugs and request features
Documentation: Check PRODUCTION_DEPLOYMENT.md for detailed deployment guide
Health Checks: Use built-in diagnostics for troubleshooting

Common Support Scenarios

API Setup: Verify Google API credentials and permissions
Performance Issues: Check cache configuration and system resources
Deployment Problems: Review Docker logs and health checks
Integration Questions: Consult MCP client documentation

Built with ❤️ for AI-powered research workflows

谷歌研究

Google Research MCP Server

🚀 Features

Core Research Capabilities

Production-Ready Features

Enhanced Content Processing

📦 Installation

Prerequisites

Quick Start (Unified Server)

Option 1: Direct Installation (No Docker Required)

Option 2: Docker Installation (Recommended for Production)

Option 3: Development Mode

⚙️ Configuration

Required Environment Variables

Optional Configuration

Validate Configuration

🔧 Usage

MCP Client Integration

Available Tools

Search Tools

Content Extraction Tools

Research & Synthesis Tools

Navigation Tools

Example Usage Scenarios

Basic Research

Comprehensive Research Report

Competitive Analysis

🛠️ Troubleshooting

Common Issues

🔴 API Authentication Errors

🔴 Rate Limiting Issues

🔴 Content Extraction Failures

🔴 Memory Issues

🔴 Docker Deployment Issues

🔴 Non-Docker Deployment Issues

Debug Mode

Non-Docker Production Deployment

Using PM2 (Recommended)

Using systemd (Linux)

Direct Node.js (Development)

Performance Optimization

Cache Tuning

Request Optimization

📊 Monitoring & Health Checks

Built-in Health Monitoring

Health Check Response

Monitoring Integration

🔄 Maintenance

Regular Maintenance Tasks

Log Management

🚀 Advanced Usage

Scaling Considerations

Custom Configurations

Integration Examples

📝 Development

Development Setup

Project Structure

🤝 Contributing

📄 License

🆘 Support

Getting Help

Common Support Scenarios

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