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securityA
license-
qualityThis MCP server performs multi-topic searches in business, news, finance, and politics using the Tavily API, providing high-quality sources and intelligent summaries.
Last updated -
1
MIT License
Supports configuration through environment variables using .env files for flexible deployment settings.
Supports formatting extracted web content as Markdown, allowing for clean, structured representation of articles with optional image inclusion.
Provides tools for discovering RSS feeds from websites, fetching entries from feeds, extracting and formatting content, searching news articles by keyword, and generating summaries of news articles from RSS sources.
MCP RSS News Agent
A FastMCP-based RSS news aggregation and processing agent that can discover, fetch, and summarize content from various RSS feeds.
Features
Discover RSS feeds from any website
Fetch entries from RSS feeds
Extract and format content from feed entries
Extract and process web content from any URL
Search news articles by keyword
Generate summaries for news articles
Get top news by category and country
Installation
Clone the repository
Install the required dependencies:
pip install -r requirements.txt
Create a
.envfile if you need environment variables (optional)
Usage
Start the MCP Server
python server.py
This will start the MCP server that exposes various RSS-related tools.
Available Tools
get_rss_feed_entries: Fetches entries from an RSS feed URL
discover_rss_feeds: Finds RSS feeds available on a website
download_feed_content: Downloads and processes the content of a feed entry
fetch_webpage: Extracts main content from any webpage URL using advanced techniques (NEW)
search_news_by_keyword: Searches news articles across multiple feeds using a keyword
create_news_summary: Creates summaries for news articles
get_top_news_from_category: Gets top news from specific categories and countries
Examples
Discover RSS Feeds on a Website
response = mcp.invoke("discover_rss_feeds", {"website_url": "https://www.theguardian.com"})
print(f"Found {response['feeds_count']} feeds")
for feed in response['feeds']:
print(f"- {feed['title']}: {feed['url']}")
Get News Articles by Keyword
response = mcp.invoke("search_news_by_keyword", {
"keyword": "climate change",
"max_results": 5
})
for article in response['results']:
print(f"- {article['title']} ({article['source']})")
print(f" Link: {article['link']}")
print()
Extract Content from Any Webpage
response = mcp.invoke("fetch_webpage", {
"url": "https://example.com/article",
"output_format": "markdown",
"include_images": True
})
print(f"Title: {response['title']}")
print(f"Extraction method: {response['extracted_by']}")
print(f"Content preview: {response['content'][:200]}...")
Get Top News from a Category
response = mcp.invoke("get_top_news_from_category", {
"category": "technology",
"country": "us",
"max_results": 3
})
for article in response['results']:
print(f"- {article['title']} ({article['source']})")
Client Example
The project includes a command-line client (client_example.py) that provides easy access to all the MCP server tools:
# Get feed entries
python client_example.py feed https://www.theguardian.com/international/rss
# Search news by keyword
python client_example.py search "artificial intelligence"
# Extract content from a webpage with advanced extraction
python client_example.py webpage https://example.com/article --format markdown --images --save
# Get news by category
python client_example.py category technology --country us
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
License
This project is licensed under the MIT License - see the LICENSE file for details.
This server cannot be installed
A FastMCP-based server that provides tools for discovering RSS feeds, fetching and processing news content, searching articles by keyword, and generating summaries across multiple news sources and categories.
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