MCP Server built for use with VS Code / Cline / Anthropic - enable google search and ability to follow links and research websites
Documentation
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 buildConfiguration
Create a .env file in the project root:
GOOGLE_API_KEY=your_google_api_key
GOOGLE_SEARCH_ENGINE_ID=your_custom_search_engine_idNote: 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:httpExpected 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 STDIOFeatures
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
| Depth | Sources | Analysis | Use Case |
|---|---|---|---|
| basic | 3 | Quick overview, 3-5 findings | Fast comparisons, initial research |
| intermediate | 5 | Comprehensive analysis, 5-7 findings | Standard research tasks |
| advanced | 8-10 | In-depth analysis, 7-10 findings, contradictions | Decision-making, comprehensive reviews |
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=trueThis 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 interfacesData Flow
Search Query → Google API → Results
↓
Deduplication
↓
Quality Scoring
↓
Content Extraction
↓
Agent Synthesis
↓
Comprehensive Research ReportAPI Reference
Tools
google_search
Search Google with advanced filtering and quality scoring.
Parameters:
query(string, required) - Search querynum_results(number, optional) - Number of results (default: 5, max: 10)site(string, optional) - Limit to specific domainlanguage(string, optional) - ISO 639-1 language codedateRestrict(string, optional) - Date filter (e.g., "m6" for last 6 months)exactTerms(string, optional) - Exact phrase matchingresultType(string, optional) - Filter by type (image, news, video)page(number, optional) - Paginationsort(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 URLformat(enum, optional) - Output format: markdown, html, text (default: markdown)full_content(boolean, optional) - Return full content (default: false)max_length(number, optional) - Maximum content lengthpreview_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 topicdepth(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
| Variable | Required | Default | Description |
|---|---|---|---|
GOOGLE_API_KEY | Yes | - | Google Custom Search API key |
GOOGLE_SEARCH_ENGINE_ID | Yes | - | Custom Search Engine ID |
ANTHROPIC_API_KEY | No | - | For Direct API mode only |
USE_DIRECT_API | No | false | Enable Direct API mode |
MCP_TRANSPORT | No | stdio | Transport mode: stdio or http |
PORT | No | 3000 | Port for HTTP mode |
Performance
Response Times
| Operation | Typical Duration | Notes |
|---|---|---|
| google_search | 1-2s | Includes quality scoring and deduplication |
| extract_webpage_content | 2-3s | Per URL |
| research_topic (basic) | 8-10s | 3 sources with agent synthesis |
| research_topic (intermediate) | 12-15s | 5 sources with comprehensive analysis |
| research_topic (advanced) | 18-25s | 8-10 sources with deep analysis |
Quality Improvements Over v2
| Metric | v2 | v3 | Improvement |
|---|---|---|---|
| Summary Quality | 2/10 | 9/10 | 350% |
| Source Diversity | Not tracked | Optimized | New |
| Duplicate Removal | 0% | ~30% | New |
| Source Ranking | Random | By quality | New |
| Focus Area Support | Generic | Dedicated | New |
| Error Helpfulness | 3/10 | 9/10 | 200% |
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
Similar MCP
Based on tags & features
Trending MCP
Most active this week