MCP News Server

MCP News Server

A server providing access to news articles from various categories including tech, data science, cybersecurity, and more, allowing retrieval and summarization of latest content.

Category
访问服务器

README

news-mcp MCP server

mcp news server

Components

Resources

The server exposes news articles stored in a database via a resource URI:

  • news://{category}/{limit}: Retrieves a list of the latest articles for a given category.
    • {category}: Filters articles by category (e.g., tech, data_science, news). See tool description for full list.
    • {limit} (optional, default 10): Specifies the maximum number of articles to return.
  • Each returned article includes title, link, published date, and source.

Prompts

The server currently does not expose any prompts. (The summarization logic exists internally but is not available via an MCP prompt).

Tools

The server implements one tool:

  • summarize_news: Retrieves raw news articles from the database, allowing the client (LLM) to summarize them.
    • Takes optional category (string) and limit (integer, default 20) arguments.
    • Returns a list of article dictionaries, each containing id, title, link, published, source, and content.
    • Available categories: tech, data_science, llm_tools, cybersecurity, linux, audio_dsp, startups, news, science, research, policy.

Configuration

The server relies on a PostgreSQL database configured via the DATABASE_URL environment variable (defaults to postgresql://localhost/mcp_news).

The news_gatherer.py script (intended to be run separately/scheduled) populates the database from various RSS feeds.

Summarization logic (internal, not exposed via MCP) uses the OpenAI API, configured via the OPENAI_API_KEY environment variable.

Other configurations (via environment variables or defaults):

  • LOOKBACK_HOURS: How far back news_gatherer.py looks for new articles (default: 6).
  • SUMMARY_WORD_TARGET: Target word count for internal summarization (default: 500).
  • MAX_ARTICLES_PER_SUMMARY: Maximum articles included in one summary batch (default: 25).
  • KEYWORD_FILTER: Keywords used by internal summarization logic.

Quickstart

Install

Claude Desktop

On MacOS: ~/Library/Application\ Support/Claude/claude_desktop_config.json On Windows: %APPDATA%/Claude/claude_desktop_config.json

<details> <summary>Development/Unpublished Servers Configuration</summary>

"mcpServers": {
  "news-mcp": {
    "command": "uv",
    "args": [
      "--directory",
      "~/dev/news-mcp",
      "run",
      "news-mcp"
    ]
  }
}

</details>

<details> <summary>Published Servers Configuration</summary>

"mcpServers": {
  "news-mcp": {
    "command": "uvx",
    "args": [
      "news-mcp"
    ]
  }
}

</details>

Development

Building and Publishing

To prepare the package for distribution:

  1. Sync dependencies and update lockfile:
uv sync
  1. Build package distributions:
uv build

This will create source and wheel distributions in the dist/ directory.

  1. Publish to PyPI:
uv publish

Note: You'll need to set PyPI credentials via environment variables or command flags:

  • Token: --token or UV_PUBLISH_TOKEN
  • Or username/password: --username/UV_PUBLISH_USERNAME and --password/UV_PUBLISH_PASSWORD

Debugging

Since MCP servers run over stdio, debugging can be challenging. For the best debugging experience, we strongly recommend using the MCP Inspector.

You can launch the MCP Inspector via npm with this command:

npx @modelcontextprotocol/inspector uv --directory ~/dev/news-mcp run news-mcp 

Upon launching, the Inspector will display a URL that you can access in your browser to begin debugging.

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选