The Google News MCP Server allows you to search and retrieve categorized Google News articles with various filtering options:
Search Capabilities: Query-based search for news articles
Smart Categorization: Automatically organizes results into topics like AI & Technology, Business, and Science & Research
Flexible Filters: Filter by topic, publication, section, or full story coverage using tokens
Global Coverage: Supports multiple languages and regions with configurable language and country codes
Error Handling: Includes robust error handling and automatic language fallback mechanisms
Provides Google News search capabilities via SerpAPI integration, supporting flexible search options, global coverage, smart categorization of news results, and multiple result types.
A Model Context Protocol (MCP) server implementation that provides Google News search capabilities via SerpAPI integration. Automatically categorizes news results and supports multiple languages and regions.
https://github.com/user-attachments/assets/1cc71c27-f840-4c94-9ab5-460d84ba4779
✨ Features
🔍 Flexible Search Options
Comprehensive search capabilities including query-based search, topic search, publication filtering and story coverage.
🌐 Global Coverage
Supports multiple languages and regions through configurable language and country codes.
📊 Smart Categorization
Automatically categorizes news results into topics like AI & Technology, Business, Science & Research, and Healthcare.
🔀 Multiple Result Types
Handles various news result types including headlines, stories, related topics and menu links.
🛠️ Robust Error Handling
Comprehensive error handling for API failures and invalid inputs, with helpful error messages.
🌍 Language Support
Automatic fallback to English for unsupported language codes with appropriate user notifications.
🔑 SerpApi Setup Guide
Before getting started, you'll need to obtain a SerpApi key. Here's how:
Visit SerpApi website and create an account
After registration, go to your Dashboard:
Locate the "API Key" section
Copy your API key
New users get 250 free API calls
API Usage Details:
Free tier: 250 searches per month
Paid plans start at $75/month for 5000 searches
Billing based on successful API calls
Multiple payment methods: Credit Card, PayPal, etc.
Usage Limits:
Request Rate: 2 requests/second
IP Restrictions: None
Concurrent Requests: 5
Response Cache Time: 1 hour
👩🔧 Solution for MCP Servers Connection Issues with NVM/NPM
Click to view my configuration solution 👉 https://github.com/modelcontextprotocol/servers/issues/76
🚀 Quick Start
Install dependencies:
Build the server:
Configure environment: Modify your
claude_desktop_config.jsonwith the following content (adjust paths according to your system):
Start the server:
Troubleshooting
Invalid API Key
Verify API key configuration in
claude_desktop_config.jsonConfirm API key is active in SERP API dashboard
Request Failures
Check network connectivity
Verify API call quota hasn't been exceeded
Validate request parameter format
Related MCP server: MCP Google Server
Running evals
The evals package loads an mcp client that then runs the index.ts file, so there is no need to rebuild between tests. You can load environment variables by prefixing the npx command. Full documentation can be found here.
📦 Installation
Installing via Smithery
To install Google News for Claude Desktop automatically via Smithery:
Installing via mcp-get
If you are using an old version of Windows PowerShell, you may need to run
Set-ExecutionPolicy Bypass -Scope Processbefore this command.
Manual Installation
@chanmeng666/google-news-server
💻 Tech Stack
📖 API Documentation
The server implements the Model Context Protocol and exposes a Google News search tool with the following parameters:
q: Search query stringgl: Country code (e.g., 'us', 'uk')hl: Language code (e.g., 'en', 'es')topic_token: Token for specific news topicspublication_token: Token for specific publishersstory_token: Token for full coverage of a storysection_token: Token for specific sections
🔧 Development
📝 License
This project is MIT licensed.
🙋♀ Author
Created and maintained by Chan Meng.
For AI Agents and LLM Crawlers
This MCP server is optimized for AI agent usage with comprehensive instructions and structured data.
Quick AI Usage Guide
AI-Friendly Features
Automatic Categorization: News results are automatically sorted into relevant categories
Structured Output: Returns formatted data optimized for AI processing
Multi-language Support: Supports various languages with automatic fallbacks
Error Handling: Comprehensive error messages and graceful degradation
Response Format
The server returns categorized news with the following structure:
Categories: AI & Technology, Business, Science & Research, Healthcare, General
Article Fields: title, source, link, date, snippet, authors
Metadata: timestamp, menu_links for related topics
Best Practices for AI Agents
Use specific, descriptive keywords for better results
Leverage automatic categorization for topic-based workflows
Implement proper error handling and retry logic
Respect API rate limits (2 requests/second)
Parse structured responses for better context understanding
Advanced Usage Patterns
News Monitoring: Use company names or stock symbols for business news
Research Exploration: Leverage topic tokens for field-specific searches
Breaking News: Use "breaking news" or "latest news" queries
Multi-language: Combine appropriate gl and hl parameters
Error Handling
Invalid API key: Check SERP_API_KEY environment variable
Unsupported language: Server auto-falls back to English
Rate limiting: Respect 2 requests/second limit
Invalid parameters: Validate parameter types before calling
Generative Engine Optimization (GEO) Features
This server includes comprehensive monitoring and optimization for AI agent usage.
Key Metrics Tracked
Citation Success Rate: Percentage of successful tool calls
AI Traffic Conversion Rate: Percentage of AI agents successfully using the tool
Query Coverage Rate: Percentage of queries returning relevant results
Response Time: Average response time for tool calls
Categorization Accuracy: Accuracy of automatic news categorization
Link Carry Rate: Percentage of responses including source links
Monitoring Configuration
Performance Optimization
Real-time metrics collection
Automated alerting for performance issues
Query pattern analysis for optimization
Agent usage tracking and analytics
Data-Driven Improvements
Continuous monitoring of AI agent satisfaction
Query success rate analysis
Response time optimization
Categorization accuracy improvements
For technical implementation details, see src/geo-metrics.ts.
AI-Optimized Metadata
This server provides comprehensive structured data for AI agents and search engines.
JSON-LD Structured Data
The server includes structured data following Schema.org standards:
Software application metadata
Feature descriptions and capabilities
Technical requirements and dependencies
Usage patterns and integration guidelines
MCP Protocol Compliance
Protocol Version: 1.0.0
Tool Name:
google_news_searchResponse Format: Structured text with categorized results
Rate Limits: 2 requests/second, 5 concurrent requests
AI Discovery Features
llms.txt: Comprehensive AI usage guide at root level
Structured Metadata: Enhanced manifest.json with AI-specific information
Error Handling: AI-friendly error messages and fallbacks
Documentation: Detailed usage examples and best practices
Integration Guidelines
Designed for seamless integration with other MCP servers
Optimized for AI agent workflows
Supports various AI platforms and frameworks
Provides clear error handling and debugging information
For complete structured data, see structured-data.json.