get_articles_by_dateLABSCO SUMMARY
Similarity search is the one you will not find elsewhere.
Date and category filters exist on every news API. Passing a block of text and getting back related articles is the query that turns a claim you are checking into the coverage around it, without having to guess which keywords the outlet used. The prompts are the other half of the design: the briefing shapes are already written, so a daily summary is one invocation rather than a query you reassemble each morning.
What it is
A Python MCP server over the API behind boring-news.fr, a French news site. It covers the four ways you actually look for a story — by when it ran, by who is in it, by what it is about, and by resemblance to something you already have — and ships prompts that turn those into daily briefings.
What you get
- Articles for a date, narrowed by category or tags —
get_articles_by_date - Articles that mention a named person —
get_articles_by_person - Articles similar to a passage of text you supply, rather than to a keyword —
get_similar_articles - The day's article groups and the categories available, so a query can be scoped before it is run —
get_article_groups,get_categories - Four ready-made briefing prompts for a given date: a tech-and-culture daily, a comprehensive summary, a highlights pass and a cultural-news pass —
daily_news,daily_news_summary,daily_news_highlights,daily_cultural_news
Requirements
No account and no key — it reads the public Boring News API. Python >= 3.8, plus httpx >= 0.25.0 and fastmcp >= 0.1.0, which come with the package. Install with pip install boring-news-mcp; the package is boring-news-mcp (version 0.5.2) and runs over stdio as a Python module. The content is French-language news, so this is a source for French coverage rather than a general news feed.
Setup effort
One command — pip install boring-news-mcp
USE CASES
01
Reading a briefing for a specific day
Invoke the daily prompt with the date and get the tech-and-culture pass assembled, rather than paging through the archive.
02
Following what is written about a person
Ask for articles mentioning them by name instead of building a keyword search that catches the wrong Martin.
03
Finding the coverage around a passage you already have
Paste the text and get similar articles back, which finds the story even when the outlet's wording differs from yours.
04
Narrowing before you search
Pull the categories and the day's article groups first, then query by date with the category that actually exists.
5 tools
Listed in project docs. Your client may show a different list.
get_articles_by_personget_similar_articlesget_article_groupsget_categoriesBEFORE YOU INSTALL
What to know first
Tools you get
5 tools named in the project's documentation. daily_news, daily_news_summary, daily_news_highlights and daily_cultural_news are prompts, not tools.
Requires
- pip on PATH
- Python >= 3.8
Where it runs
The documented client runs the server on your machine.
INSTALLATION
Connect your client
Server setup
TERMINAL
pip install boring-news-mcpMCP Clients
Claude Desktop
CLAUDE DESKTOP · JSON
{
"mcpServers": {
"boringnews": {
"command": "python",
"args": [
"-m",
"boring_news_mcp"
]
}
}
}
