Google News MCP

A Model Context Protocol (MCP) server that exposes Google News RSS feeds as MCP tools, allowing AI assistants (Claude, GPT-4, etc.) to access real-time news data with automatic URL decoding, concurrent processing, and intelligent caching.

Key Features

Async & Concurrent - All operations run asynchronously with concurrent URL decoding for maximum performance
Smart Caching - LRU cache (1024 entries) for fast repeated URL decodings
Batch URL Decoding - Decode multiple Google News URLs in parallel
Clean Summaries - Extracts plain text from HTML summaries with decoded article links
Token-Oriented Object Notation (TOON) - Support for a compact, token-efficient response format (30-60% reduction)
Multi-language Support - Configure for any language/country combination
Advanced Search - Full support for Google News search operators (site:, when:, intitle:, etc.)
Page Extraction - Fetch and summarize full article content using Jina Reader and Groq

Tool Overview

Total: 8 tools

Quick Start

Installation

Option 1: Using uv (recommended)

# Clone the repository
git clone https://github.com/moltrus/google-news-mcp.git
cd google-news-mcp

# Install with uv
uv sync

Option 2: Using pip with virtual environment

# Clone the repository
git clone https://github.com/moltrus/google-news-mcp.git
cd google-news-mcp

# Create virtual environment
python -m venv .venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate

# Install in development mode
pip install -e .

For Global Usage (Any Method)

To use the google-news-mcp command globally from anywhere:

pip install -e .

This installs the command-line entry point system-wide, allowing you to run google-news-mcp from any directory.

Configuration

Create a .env file based on .env.example:

# RSS Preferences
GOOGLE_NEWS_LANGUAGE=en
GOOGLE_NEWS_COUNTRY=US

# Response Optimization
# Options: "json" (standard) or "toon" (token-optimized)
RESPONSE_FORMAT=json

# Fetching & Summarization
JINA_API_KEY=your_jina_key
GROQ_API_KEY=your_groq_key
GROQ_MODEL=qwen/qwen3-32b

Running the Server

google-news-mcp

Or directly:

python -m google_news_mcp.server

Tool Documentation

get_top_headlines

Fetch the latest top headlines for a country.

Parameters:

• language (string, optional): Language code (e.g., 'en', 'fr', 'es'). Defaults to GOOGLE_NEWS_LANGUAGE env var.

• country (string, optional): Country code (e.g., 'US', 'GB', 'JP'). Defaults to GOOGLE_NEWS_COUNTRY env var.

Returns:

{
  "title": "Google News",
  "link": "https://news.google.com",
  "description": "Latest news",
  "entries": [
    {
      "title": "Article Title",
      "link": "https://source.com/article",
      "published": "2026-03-31T10:00:00Z",
      "summary": "Article Title (https://source.com/article)\nAnother Article (https://another.com/news)",
      "source": "Source Name"
    }
  ]
}

Notes:

• Articles are sorted by relevance (Google News default)

• URLs are automatically decoded from Google News redirects

• Summaries contain extracted links in plain text format

get_category_feed

Get news headlines for a specific category.

Parameters:

• category (string, required): News category. Valid values:

  • WORLD - International news

  • NATION - National/local headlines

  • BUSINESS - Business & finance

  • TECHNOLOGY - Tech & AI

  • ENTERTAINMENT - Entertainment & pop culture

  • SPORTS - Sports

  • SCIENCE - Science & research

  • HEALTH - Health & medicine

• language (string, optional): Language code. Defaults to config.

• country (string, optional): Country code. Defaults to config.

Returns: Same as get_top_headlines

Examples:

get_category_feed(category="TECHNOLOGY")
get_category_feed(category="BUSINESS", country="UK")

get_search_feed

Search Google News with keyword queries and advanced operators.

Parameters:

• query (string, required): Search query with optional operators

• language (string, optional): Language code. Defaults to config.

• country (string, optional): Country code. Defaults to config.

Supported Search Operators:

• Exact phrase: "Artificial Intelligence" (must match exactly)

• Exclude term: -apple (exclude articles with "apple")

• Site-specific: site:techcrunch.com (only from domain)

• Time range (relative): when:1h, when:24h, when:7d, when:30d, when:1y, when:1m

• Time range (absolute): after:2026-01-01, before:2026-03-31

• Title search: intitle:merger (term appears in headline only)

• Boolean OR: Tesla OR SpaceX (either term)

• Combinations: "GPT-4" site:openai.com when:7d (all together)

Returns: Same as get_top_headlines (max ~100 articles)

Query Examples:

"OpenAI Sora"                                # Exact phrase
AI -hype                                     # Include AI, exclude hype
site:arxiv.org quantum computing             # From academic site
when:1h breaking                             # Last hour
when:24h -rumor Bitcoin                      # Last 24h, exclude rumors
after:2026-03-01 before:2026-03-31 merger    # Date range
intitle:IPO tech companies                   # IPO in headline
SpaceX OR Blue Origin                        # Either company OR other

Important: Date filters work on a daily basis (not hourly/minute precision).

get_geo_feed

Get news for a specific geographic location.

Parameters:

• location (string, required): City, state, region, or country (e.g., 'San Francisco', 'California', 'Japan')

• language (string, optional): Language code. Defaults to config.

• country (string, optional): Country code. Defaults to config.

Returns: Same as get_top_headlines

Examples:

get_geo_feed(location="New York")
get_geo_feed(location="London", language="en")
get_geo_feed(location="Tokyo", country="JP")

fetch_content

Fetch clean page content from a URL using Jina Reader API, with optional summarization via Groq.

Parameters:

• url (string, required): Absolute URL to fetch (must start with http:// or https://)

• summarize (boolean, optional): If true, returns a concise summary via Groq and omits the full raw content to save tokens. Defaults to false.

Returns:

{
  "url": "https://example.com/article",
  "reader_url": "https://r.jina.ai/https://example.com/article",
  "content": "Full article text...",
  "summary": "Concise summary points...",
  "summary_model": "qwen/qwen3-32b",
  "summary_error": "Error message if summarization fails"
}

Notes:

• Token Efficiency: When summarize is true, the content field is automatically removed from the response to prevent context window bloat.

• Environment Variables:

  • JINA_API_KEY: Required for content extraction.

  • GROQ_API_KEY: Required for summarization.

  • GROQ_MODEL: Optional. Specific model to use (defaults to qwen/qwen3-32b).

decode_google_news_url

Decode multiple Google News URLs to their actual article destinations in parallel.

Parameters:

• urls (list of strings, required): Array of Google News redirect URLs to decode

Returns:

{
  "decoded_urls": [
    {
      "original_url": "https://news.google.com/articles/CBMi8wFAUU...",
      "decoded_url": "https://techcrunch.com/2026/03/31/ai-news"
    },
    {
      "original_url": "https://news.google.com/articles/CBMixAFAUU...",
      "decoded_url": "https://theverge.com/2026/3/31/10987654"
    }
  ]
}

Performance:

• All URLs decoded concurrently (no sequential delays)

• Results cached for repeat lookups (instant on cache hit)

• LRU cache with 1024 entry limit

Examples:

decode_google_news_url(urls=[
  "https://news.google.com/articles/CBMi8wFAUU...",
  "https://news.google.com/articles/CBMixAFAUU...",
  "https://news.google.com/articles/CBMi5gFAUU..."
])

get_topic_feed

Get news for a specific trending topic by its topic ID.

Google News tracks trending topics as hashes (e.g., companies, events, recurring themes).

Parameters:

• topic_id (string, required): Google News topic hash identifier

• language (string, optional): Language code. Defaults to config.

• country (string, optional): Country code. Defaults to config.

Returns: Same as get_top_headlines

Common Topic IDs:

• CAAqKAgKIiJDQkFTRXdvS0wyMHZNSFp3YWpSZlloSUZaVzR0UjBJb0FBUAE - Cryptocurrencies

• Find more by exploring Google News and checking the topic parameter in URLs

Examples:

get_topic_feed(topic_id="CAAqKAgKIiJDQkFTRXdvS0wyMHZNSFp3YWpSZlloSUZaVzR0UjBJb0FBUAE")

list_categories

Get the list of available news categories.

Parameters: None

Returns:

{
  "categories": [
    "WORLD",
    "NATION",
    "BUSINESS",
    "TECHNOLOGY",
    "ENTERTAINMENT",
    "SPORTS",
    "SCIENCE",
    "HEALTH"
  ]
}

Architecture

Performance Optimizations

1. Async/Await - All I/O operations (HTTP, decoding) are non-blocking

2. Concurrent Processing - Multiple URLs and entries processed in parallel via asyncio.gather()

3. LRU Cache (1024 entries) - Decoded URLs cached at function level

4. In-Memory Dictionary Cache - Additional fast lookup cache for decoded URLs

5. Batch Operations - decode_google_news_url processes lists of URLs concurrently

Summary Format

Article summaries are extracted from HTML and returned as plain text with decoded links:

Article Title 1 (https://original-source.com/article1)
Image caption link (https://image-source.com/photo)
Article Title 2 (https://original-source.com/article2)

HTML tags, CDATA wrappers, and entities are stripped for clean, readable text.

Usage Examples

1. Get breaking news in the last hour

get_search_feed(query="when:1h breaking", country="US")

2. Decode multiple article URLs at once

decode_google_news_url(urls=[
  "https://news.google.com/articles/CBMi8wFAUU...",
  "https://news.google.com/articles/CBMixAFAUU..."
])

3. Tech news from specific source

get_search_feed(query="site:techcrunch.com AI")

4. Local news for a city

get_geo_feed(location="San Francisco")

5. Search with date range

get_search_feed(query="SpaceX after:2026-03-01 before:2026-03-31")

6. Get health news

get_category_feed(category="HEALTH")

7. Trending cryptocurrency news

get_topic_feed(topic_id="CAAqJggKIiBDQkFTRWdvSUwyMHZNR3d5YldFeVpYVXVhVzV6U0FpQkFQAQ")

8. Fetch and summarize a full article

fetch_content(url="https://techcrunch.com/article-url", summarize=true)

Token Efficiency & TOON

This server supports Token-Oriented Object Notation (TOON), a compact data format designed specifically for LLMs.

Why use TOON?

Standard JSON can be verbose for LLMs due to repeated keys and punctuation. TOON reduces token usage by 30-60% by:

• Defining keys once for arrays of objects (tabular format).

• Removing unnecessary braces, brackets, and quotes.

• Using indentation and simple delimiters.

Configuration

To enable TOON globally for all tool responses, set the following in your .env:

RESPONSE_FORMAT=toon

Comparison

Limitations

1. Result limit: Google News RSS returns max ~100 articles per request

2. Sorting: Default is relevance. Use when: filters for temporal ordering

3. Date precision: Filters work on daily basis, not by hour/minute

4. Rate limiting: No API keys needed for RSS, but Jina Reader and Groq have their own limits/quotas

5. Content Extraction: fetch_content depends on Jina Reader's ability to parse the target site

6. Topic IDs: Must be discovered from Google News URLs; no lookup API

License

MIT