global-news-mcp-server by press-monitor - MCP Server

Global News MCP Server - 200 Countries, 100+ Languages. Millions of News Items Everyday!

🌍 Real-Time Global News Intelligence for AI Agents & Applications

News MCP Server is a production-ready Model Context Protocol (MCP) server that provides real-time, multilingual news intelligence from 200+ countries and 18+ languages. Built for AI agents, autonomous applications, and enterprise workflows, it delivers structured news data with advanced filtering, caching, and framework integrations.

Perfect for LLM applications, AI agents, research platforms, compliance monitoring, brand reputation tracking, and market intelligence.

🚀 Quick Start

Installation

# Core installation
pip install news-mcp-server

# Full installation with Redis caching & monitoring
pip install news-mcp-server[full]

# AI framework integrations (LangChain, CrewAI)
pip install news-mcp-server[frameworks]

# Enterprise cloud features
pip install news-mcp-server[cloud]

# Everything included
pip install news-mcp-server[all]

Basic Usage

# Start the MCP server
news-mcp-server run

# Server runs on http://localhost:3000
# Health check: http://localhost:3000/health
# Metrics: http://localhost:3000/metrics

Environment Setup

# Required: Press Monitor API credentials
# Get your API key: https://aws.amazon.com/marketplace/pp/prodview-vpx4cz3ekl3b2?sr=0-2&ref_=beagle&applicationId=AWSMPContessa
export PRESS_MONITOR_API_KEY="your_secret_key:subscription_id"

# Optional: Server authentication
export NEWS_MCP_API_KEY="your_server_api_key"

# Optional: Redis for enterprise caching
export REDIS_URL="redis://localhost:6379/0"

🎯 Key Features

🌐 Global News Coverage

200+ countries with real-time monitoring
18+ languages including English, Spanish, French, Arabic, Chinese, Hindi
Thousands of sources: newspapers, news websites, blogs, select social channels

🤖 AI-Ready Integration

MCP (Model Context Protocol) for seamless AI agent integration
Structured JSON responses optimized for LLM consumption
Built-in LangChain, CrewAI, AutoGPT integrations
OpenAI, Claude, GPT-4 compatible

📊 Rich Data & Metadata

Headlines, briefs, full-text articles
Images, entities, sentiment analysis
Wikidata-aligned metadata for advanced analytics
Geographic and temporal filtering

⚡ Production-Ready

High-performance Redis caching
Prometheus metrics & health checks
Rate limiting & circuit breakers
Docker & Kubernetes ready

📖 API Endpoints

Core MCP Methods

Method	Description	Use Case
`news_headlines`	Get news headlines with titles, URLs, sources	Quick news updates, notifications
`news_briefs`	Get news summaries with descriptions	Content feeds, dashboards
`news_fulltext`	Get complete articles with full content	Research, analysis, archiving
`news_fulltext_metadata`	Get articles with entities, Wikidata IDs	Advanced analytics, compliance
`news_headlines_translated`	Get translated headlines	Multilingual applications

Example MCP Request

{
  "jsonrpc": "2.0",
  "id": "1",
  "method": "news_headlines",
  "params": {
    "query_text": "artificial intelligence breakthrough",
    "country_code": "US",
    "lang_code": "en",
    "count": 10,
    "sort": "latest"
  }
}

Python SDK Usage

from news_mcp_server.api.client import NewsMCPClient

async with NewsMCPClient(
    server_url="http://localhost:3000",
    api_key="your_api_key"
) as client:

    # Get AI news headlines
    headlines = await client.get_headlines(
        query="machine learning",
        country_code="US",
        count=5
    )

    for article in headlines.items:
        print(f"📰 {article.title}")
        print(f"🏢 {article.source}")
        print(f"🔗 {article.url}\n")

🤖 AI Framework Integrations

LangChain Integration

from langchain.agents import initialize_agent, AgentType
from langchain.llms import OpenAI
from news_mcp_server.plugins.langchain import LangChainPlugin

# Initialize news tool
plugin = LangChainPlugin()
await plugin.initialize()

news_tool = await plugin.create_tool(
    server_url="http://localhost:3000",
    api_key="your_api_key"
)

# Create AI agent with news capabilities
llm = OpenAI(temperature=0)
agent = initialize_agent(
    tools=[news_tool],
    llm=llm,
    agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION
)

# Ask agent to find and analyze news
result = agent.run("""
Find recent news about AI breakthroughs in healthcare
and provide a summary of key developments
""")

CrewAI Integration

from crewai import Agent, Task, Crew
from news_mcp_server.plugins.crewai import CrewAIPlugin

# Create news-powered AI agent
news_agent = Agent(
    role='News Analyst',
    goal='Find and analyze relevant news for insights',
    backstory='Expert at finding and interpreting news trends',
    tools=[news_tool]
)

# Define analysis task
analysis_task = Task(
    description="Find news about renewable energy investments and analyze trends",
    agent=news_agent
)

# Execute with crew
crew = Crew(agents=[news_agent], tasks=[analysis_task])
result = crew.kickoff()

🔧 Installation Variants

Minimal Installation

pip install news-mcp-server
# Core MCP server only (~20MB)

Production Installation

pip install news-mcp-server[full]
# Includes Redis caching, monitoring, health checks

AI Development

pip install news-mcp-server[frameworks]
# Includes LangChain, CrewAI integrations

Enterprise Cloud

pip install news-mcp-server[cloud]
# Includes AWS, Azure, GCP integrations

🚀 Deployment Options

Local Development

# Start with auto-reload
news-mcp-server run --reload

# With debug logging
news-mcp-server run --log-level debug

Docker Deployment

# Pull and run
docker run -p 3000:3000 \
  -e PRESS_MONITOR_API_KEY=your_key \
  news-mcp-server:latest

Production Configuration

# With Redis and monitoring
news-mcp-server run \
  --config production.json \
  --workers 4

🎯 Use Cases

🤖 AI Agent Applications

Autonomous research agents with real-time news access
Content generation with current events context
Market analysis bots for trading and investment
Compliance monitoring for regulatory changes

📊 Enterprise Intelligence

Brand reputation monitoring across global media
Competitive intelligence and market trends
Risk assessment and geopolitical analysis
Executive briefings with AI-powered summaries

🔬 Research & Analytics

Academic research with structured news data
Sentiment analysis on global events
Social listening and trend analysis
Policy impact assessment

🏢 Business Applications

CRM integration with relevant industry news
Marketing intelligence and campaign optimization
Sales enablement with prospect context
Customer success with account-relevant updates

🔍 Search & Filtering

Geographic Filtering

# US technology news
headlines = await client.get_headlines(
    query="technology innovation",
    country_code="US"
)

# European markets
headlines = await client.get_headlines(
    query="financial markets",
    country_code="DE,FR,IT"
)

Language Support

# Spanish language news
headlines = await client.get_headlines(
    query="inteligencia artificial",
    lang_code="es"
)

# Multilingual search
headlines = await client.get_headlines(
    query="climate change",
    lang_code="en,fr,de"
)

Advanced Queries

# Time-sensitive searches
headlines = await client.get_headlines(
    query="earnings report",
    sort="latest",
    count=50
)

# Relevance-based ranking
headlines = await client.get_headlines(
    query="artificial intelligence breakthrough",
    sort="relevance",
    count=20
)

📈 Performance & Monitoring

Built-in Monitoring

Prometheus metrics at /metrics
Health checks at /health
Request/response tracking
Cache hit rate monitoring

Caching Strategy

Redis integration for enterprise performance
Memory fallback for development
Configurable TTL (default: 5 minutes)
Automatic cache invalidation

Rate Limiting

Configurable limits (default: 60/minute)
Burst protection (100 requests/30s)
Client-specific quotas
Graceful degradation

🛠️ Configuration

Configuration File (`config.json`)

{
  "server": {
    "host": "0.0.0.0",
    "port": 3000,
    "log_level": "info"
  },
  "cache": {
    "provider": "redis",
    "redis_url": "redis://localhost:6379/0",
    "ttl": 300,
    "enabled": true
  },
  "monitoring": {
    "enabled": true,
    "metrics_endpoint": "/metrics",
    "health_endpoint": "/health"
  },
  "security": {
    "rate_limiting": {
      "enabled": true,
      "requests_per_minute": 60
    }
  }
}

Environment Variables

# Core configuration
PRESS_MONITOR_API_KEY=your_secret_key:subscription_id
NEWS_MCP_API_KEY=your_server_api_key

# Performance tuning
REDIS_URL=redis://localhost:6379/0
CACHE_TTL=300
MAX_WORKERS=4

# Security
RATE_LIMIT_ENABLED=true
REQUESTS_PER_MINUTE=60

🔐 Security Features

API key authentication for server access
Bearer token validation for Press Monitor API
Rate limiting to prevent abuse
Input validation and sanitization
CORS configuration for web applications
Request logging for audit trails

📚 Documentation & Support

Resources

API Documentation - Comprehensive API reference
Open API Schema - API schema specification
Press Monitor Website - Official vendor website
GitHub Repository - Source code and issues
Examples Collection - Integration examples

Community Support

GitHub Issues - Bug reports and feature requests
Discord Server - Real-time community help
Stack Overflow - Tag: news-mcp-server
Email Support - support@pressmonitor.com (1-2 working days response time)

🏗️ Advanced Features

Custom Plugins

from news_mcp_server.plugins.base import FrameworkPlugin

class CustomNewsPlugin(FrameworkPlugin):
    async def create_tool(self, server_url, api_key):
        # Custom integration logic
        pass

Webhook Integration

# Real-time news alerts
await client.setup_webhook(
    url="https://yourapp.com/news-webhook",
    events=["new_article", "trending_topic"],
    filters={"query": "your_keywords"}
)

Batch Processing

# Process multiple queries efficiently
queries = [
    {"query_text": "AI", "country_code": "US"},
    {"query_text": "blockchain", "country_code": "UK"},
    {"query_text": "sustainability", "country_code": "DE"}
]

results = await client.batch_search(queries)

🏆 Why Choose News MCP Server?

✅ Production Ready

Battle-tested in enterprise environments
99.9% uptime SLA available
Comprehensive monitoring and alerting
Horizontal scaling support

✅ Developer Friendly

One-line installation with pip
Extensive documentation and examples
Active community and support
Framework-agnostic design

✅ AI Optimized

Purpose-built for LLM applications
Structured data perfect for AI consumption
Built-in framework integrations
Optimized for agent workflows

✅ Global Scale

200+ countries covered
18+ languages supported
Real-time data processing
Enterprise-grade infrastructure

📊 Pricing & Usage

Free Tier

Up to 1,000 requests/month
Basic news headlines and briefs
Community support
Perfect for development and testing

Professional Tier ($49/month)

Up to 50,000 requests/month
Full-text articles and metadata
Redis caching included
Email support

Enterprise Tier (Custom)

Unlimited requests
SLA and dedicated support
Custom integrations
On-premise deployment options

🚀 Get Started Today

# Install the package
pip install news-mcp-server[full]

# Get your API key from Press Monitor
# https://aws.amazon.com/marketplace/pp/prodview-vpx4cz3ekl3b2?sr=0-2&ref_=beagle&applicationId=AWSMPContessa

# Set up environment
export PRESS_MONITOR_API_KEY="your_key"

# Start the server
news-mcp-server run

# Test with a simple request
curl -X POST http://localhost:3000/mcp \
  -H "Content-Type: application/json" \
  -d '{
    "jsonrpc": "2.0",
    "id": "1",
    "method": "news_headlines",
    "params": {
      "query_text": "artificial intelligence",
      "count": 5
    }
  }'

Transform your AI applications with real-time global news intelligence. Start building today! 🚀

Keywords: news API, MCP server, AI agent integration, global news search, real-time media monitoring, LangChain news tool, CrewAI integration, multilingual news API, enterprise news intelligence, Python news API, AI-powered media monitoring, autonomous agent tools