GenAI News Assistant MCP Server
@uriyahav
GenAI News Assistant MCP Server について
概要はまだありません
基本情報
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{
"mcpServers": {
"MCP_SSE_Server": {
"command": "docker",
"args": [
"build",
"-t",
"news-assistant-python",
"."
]
}
}
}ツール
ツールは検出されませんでした
ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。
概要
What is GenAI News Assistant MCP Server?
It is a Model Context Protocol (MCP) server template that provides tools for fetching and analyzing news information using NewsAPI.org and a Large Language Model. It is intended for developers building AI assistants that need to search and understand recent news.
How to use GenAI News Assistant MCP Server?
Set up by cloning the repository, obtaining API keys for NewsAPI.org and an LLM, then build and run the Docker container for either the Python or TypeScript implementation. The server exposes MCP tools for news search and analysis and can be tested locally using the MCP Inspector.
Key features of GenAI News Assistant MCP Server
- Fetches news via NewsAPI.org
- Analyzes articles using an LLM
- Extracts structured information and sentiment
- Implements three MCP tools: search, extract info, extract key info/sentiment
- Available in both Python and TypeScript
- Runs inside Docker for easy deployment
Use cases of GenAI News Assistant MCP Server
- Monitor news articles for specific topics or queries
- Extract key entities and sentiment from news articles
- Automate news summarization and analysis in AI workflows
FAQ from GenAI News Assistant MCP Server
What API keys are required?
You need a NewsAPI.org API key and an LLM API key, set as environment variables NEWS_API_KEY and LLM_API_KEY.
How do I run the server?
Build the Docker image for your chosen implementation (Python or TypeScript) and run the container, passing the API keys as environment variables.
What MCP tools does it provide?
Three tools: search_news (search for recent articles), extract_information_from_article (extract structured info from an article), and extract_key_info_and_sentiment (analyze key entities and sentiment).
What are the runtime requirements?
Docker is required; no direct dependency on Python or Node.js if using Docker. The server listens on port 3000 by default.
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