The Google Search MCP Server enables AI models to perform Google searches and analyze webpage content programmatically.
Google Search: Conduct searches with advanced filters (country, language, date range, safe search) and control result count (up to 10).
Webpage Content Extraction: Extract readable content from public webpages in various formats (markdown, HTML, plain text), removing clutter like ads and navigation.
Content Analysis: Get detailed insights including titles, descriptions, summaries, and statistics (word count, character count).
Batch Processing: Extract and analyze content from up to 5 webpages simultaneously in a single request.
Integration: Seamlessly integrate with AI models using MCP-compliant interfaces.
Error Handling: Provides detailed error messages for troubleshooting.
Provides Google search capabilities to AI models through an MCP server interface, allowing for advanced search queries with filtering options for date, language, country, and safe search
Integrates with Google Cloud Platform for API credentials and Custom Search capabilities needed to power the Google search functionality
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
Related MCP server: searchAPI-mcp
Quick Start
Prerequisites
Node.js 18 or higher
Google Cloud Platform account with Custom Search API enabled
Google Custom Search Engine ID
Installation
Configuration
Create a .env file in the project root:
Note: No Anthropic API key is required. The server uses agent-based synthesis that leverages your existing Claude session.
Running the Server
Expected output:
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
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
Returns:
3 high-quality sources
Brief overview (2-3 paragraphs)
3-5 key findings
Quality metrics
Comprehensive Research with Focus Areas
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
Returns:
Quality-scored results
Duplicate removal report
Source type classification
Authority ratings
Content Extraction
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:
Research Gathering - MCP server searches, deduplicates, and ranks sources
Content Extraction - Full content extracted from top sources
Agent Prompt Generation - All research data packaged into structured prompt
Agent Launch - Claude Code automatically launches agent with research data
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:
This bypasses agent mode and calls the Anthropic API directly from the MCP server.
Architecture
Services
Data Flow
API 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 |
| Yes | - | Google Custom Search API key |
| Yes | - | Custom Search Engine ID |
| No | - | For Direct API mode only |
| No | false | Enable Direct API mode |
| No | stdio | Transport mode: stdio or http |
| 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:
Verify server shows "AGENT MODE" on startup
Check for
[AGENT_SYNTHESIS_REQUIRED]in responseEnsure using v3:
npm run start:v3Rebuild:
npm run build
Quality Scores Missing
Symptoms: Search results don't show quality scores
Solutions:
Confirm running v3, not v2
Check server startup output
Verify no TypeScript compilation errors
No Results Found
Solutions:
Verify Google API key is valid
Check Custom Search Engine ID
Ensure search engine has indexing enabled
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:
Code follows existing style conventions
All tests pass:
npm run buildDocumentation is updated
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