Google Research MCP Server

Version 3.0.0 - Enhanced research synthesis with intelligent source quality assessment and deduplication.

An advanced Model Context Protocol (MCP) server that provides comprehensive Google search capabilities, webpage content extraction, and AI-powered research synthesis. Built for Claude Code, Claude Desktop, and other MCP-compatible clients.

Overview

This MCP server transforms Google search into a powerful research tool by:

• Intelligent Source Ranking - Automatically scores sources by authority, recency, and credibility
• Deduplication - Removes duplicate URLs and similar content across search results
• Agent-Based Synthesis - Leverages your existing Claude session to synthesize research findings
• Focus Area Analysis - Provides dedicated analysis for specific aspects of your research topic
• Quality Metrics - Tracks source diversity, authority, and content freshness

Quick Start

Prerequisites

• Node.js 18 or higher
• Google Cloud Platform account with Custom Search API enabled
• Google Custom Search Engine ID

Installation

# Clone the repository
git clone 
cd Google-Research-MCP

# Install dependencies
npm install

# Build the project
npm run build

Configuration

Create a .env file in the project root:

GOOGLE_API_KEY=your_google_api_key
GOOGLE_SEARCH_ENGINE_ID=your_custom_search_engine_id

Note: No Anthropic API key is required. The server uses agent-based synthesis that leverages your existing Claude session.

Running the Server

# Start v3 server (recommended)
npm run start:v3

# For HTTP mode
npm run start:v3:http

Expected output:

============================================================
Google Research MCP Server v3.0.0 (Enhanced)
============================================================
✓ Source quality assessment
✓ Deduplication
✓ AI synthesis: AGENT MODE (Claude will launch agents)
  └─ No API key needed - uses your existing Claude session
✓ Focus area analysis
✓ Enhanced error handling
✓ Cache metadata
============================================================
Server running on STDIO

Features

Core Capabilities

1. Advanced Google Search

• Full-text search with quality scoring
• Domain filtering and date restrictions
• Result categorization (academic, official docs, news, forums, etc.)
• Automatic deduplication of results
• Source authority ranking

2. Content Extraction

• Clean content extraction from web pages
• Multiple output formats (Markdown, HTML, plain text)
• Configurable preview lengths
• Batch extraction support (up to 5 URLs)
• Automatic content summarization

3. Research Synthesis

• Agent-based research analysis
• Comprehensive source synthesis
• Focus area breakdowns
• Contradiction detection
• Actionable recommendations
• Quality metrics reporting

Research Depth Levels

Usage Examples

Basic Research

research_topic({
  topic: "WebAssembly performance optimization",
  depth: "basic"
})

Returns:

• 3 high-quality sources
• Brief overview (2-3 paragraphs)
• 3-5 key findings
• Quality metrics

Comprehensive Research with Focus Areas

research_topic({
  topic: "Kubernetes security",
  depth: "advanced",
  focus_areas: ["RBAC", "network policies", "pod security"],
  num_sources: 8
})

Returns:

• 8 authoritative sources
• In-depth executive summary
• 7-10 detailed findings
• Common themes across sources
• Dedicated analysis for each focus area
• Contradictions between sources
• Actionable recommendations
• Comprehensive quality metrics

Targeted Search

google_search({
  query: "docker container security best practices",
  num_results: 10,
  dateRestrict: "y1",  // Last year only
  site: "github.com"   // Limit to GitHub
})

Returns:

• Quality-scored results
• Duplicate removal report
• Source type classification
• Authority ratings

Content Extraction

extract_webpage_content({
  url: "https://kubernetes.io/docs/concepts/security/",
  format: "markdown",
  max_length: 5000,
  preview_length: 300
})

Returns:

• Clean extracted content
• Metadata (title, description, author)
• Word count and statistics
• Configurable preview
• Cache information

Agent Mode

How It Works

Agent Mode is the default synthesis method. Instead of requiring a separate Anthropic API key, it uses your existing Claude session:

1. Research Gathering - MCP server searches, deduplicates, and ranks sources
2. Content Extraction - Full content extracted from top sources
3. Agent Prompt Generation - All research data packaged into structured prompt
4. Agent Launch - Claude Code automatically launches agent with research data
5. Synthesis - Agent analyzes sources and generates comprehensive report

Benefits

• No Additional API Key - Uses your existing Claude subscription
• Full Context - Agent has access to conversation history
• Transparent Process - See agent analysis in real-time
• Same Quality - Uses same Claude model you're already using

Alternative: Direct API Mode

For automated workflows or scripts, you can use Direct API mode:

# .env
ANTHROPIC_API_KEY=your_anthropic_api_key
USE_DIRECT_API=true

This bypasses agent mode and calls the Anthropic API directly from the MCP server.

Architecture

Services

src/
├── google-search-v3.ts              # Main MCP server (v3)
├── services/
│   ├── google-search.service.ts     # Google Custom Search integration
│   ├── content-extractor.service.ts # Web content extraction
│   ├── source-quality.service.ts    # Source ranking and scoring
│   ├── deduplication.service.ts     # Duplicate detection
│   └── research-synthesis.service.ts # Agent-based synthesis
└── types.ts                          # TypeScript interfaces

Data Flow

Search Query → Google API → Results
                              ↓
                         Deduplication
                              ↓
                         Quality Scoring
                              ↓
                         Content Extraction
                              ↓
                         Agent Synthesis
                              ↓
                    Comprehensive Research Report

API Reference

Tools

google_search

Search Google with advanced filtering and quality scoring.

Parameters:

• query (string, required) - Search query
• num_results (number, optional) - Number of results (default: 5, max: 10)
• site (string, optional) - Limit to specific domain
• language (string, optional) - ISO 639-1 language code
• dateRestrict (string, optional) - Date filter (e.g., "m6" for last 6 months)
• exactTerms (string, optional) - Exact phrase matching
• resultType (string, optional) - Filter by type (image, news, video)
• page (number, optional) - Pagination
• sort (string, optional) - Sort by relevance or date

Returns:

• Ranked search results with quality scores
• Deduplication statistics
• Source categorization
• Pagination info
• Cache metadata

extract_webpage_content

Extract clean content from a webpage.

Parameters:

• url (string, required) - Target URL
• format (enum, optional) - Output format: markdown, html, text (default: markdown)
• full_content (boolean, optional) - Return full content (default: false)
• max_length (number, optional) - Maximum content length
• preview_length (number, optional) - Preview length (default: 500)

Returns:

• Extracted content
• Metadata (title, description, author)
• Statistics (word count, character count)
• Content summary
• Cache information

extract_multiple_webpages

Batch extract content from multiple URLs (max 5).

Parameters:

• urls (array, required) - Array of URLs (max 5)
• format (enum, optional) - Output format

Returns:

• Extracted content per URL
• Error details for failed extractions
• Cache metadata

research_topic

Comprehensive research with AI synthesis.

Parameters:

• topic (string, required) - Research topic
• depth (enum, optional) - Analysis depth: basic, intermediate, advanced (default: intermediate)
• num_sources (number, optional) - Number of sources (default: varies by depth)
• focus_areas (array, optional) - Specific aspects to analyze

Returns:

• Executive summary
• Key findings with citations
• Common themes
• Focus area analysis (if specified)
• Contradictions between sources
• Recommendations
• Quality metrics (source diversity, authority, freshness)
• Source list with quality scores

Configuration Options

Environment Variables

Performance

Response Times

Quality Improvements Over v2

Troubleshooting

Agent Mode Not Working

Symptoms: Research returns basic concatenation instead of synthesis

Solutions:

1. Verify server shows "AGENT MODE" on startup
2. Check for [AGENT_SYNTHESIS_REQUIRED] in response
3. Ensure using v3: npm run start:v3
4. Rebuild: npm run build

Quality Scores Missing

Symptoms: Search results don't show quality scores

Solutions:

1. Confirm running v3, not v2
2. Check server startup output
3. Verify no TypeScript compilation errors

No Results Found

Solutions:

1. Verify Google API key is valid
2. Check Custom Search Engine ID
3. Ensure search engine has indexing enabled
4. Try broader search terms

Documentation

• QUICK-START.md - Fast setup guide (2 minutes)
• AGENT-MODE.md - Comprehensive agent mode documentation
• SETUP-V3.md - Detailed setup and testing guide
• README-V3.md - Feature documentation and comparisons
• tool-evaluation-report.md - Detailed analysis of improvements
• implementation-guide.md - Code implementation details

Version History

v3.0.0 (Current)

• Agent-based synthesis (no API key required)
• Source quality assessment and ranking
• Comprehensive deduplication
• Focus area analysis
• Enhanced error handling with suggestions
• Cache metadata transparency
• Consistent preview lengths
• Research depth differentiation

v2.0.0

• HTTP transport support
• Batch webpage extraction
• Basic research synthesis
• Content categorization

v1.0.0

• Initial release
• Google Custom Search integration
• Basic content extraction

Contributing

Contributions are welcome. Please ensure:

1. Code follows existing style conventions
2. All tests pass: npm run build
3. Documentation is updated
4. Commit messages are descriptive

License

See LICENSE file for details.

Support

For issues, questions, or feature requests, please open an issue on GitHub.

Credits

• Google Custom Search API - Search functionality
• Anthropic Claude - AI-powered research synthesis
• Mozilla Readability - Content extraction
• MCP SDK - Model Context Protocol integration

Status: Production Ready Version: 3.0.0 Last Updated: 2025-11-07