The Verge News MCP Server
The Verge 新闻 MCP 服务器
MCP 服务器提供从 The Verge 的 RSS 提要中获取和搜索新闻的工具。
特征
从 The Verge 获取今天的新闻
从 The Verge 过去一周随机获取新闻
按关键字搜索新闻文章
Related MCP server: News Aggregator MCP Server
安装
# Clone the repository
git clone https://github.com/manimohans/verge-news-mcp.git
cd verge-news-mcp
# Install dependencies
npm install
# Build the project
npm run build用法
运行服务器
npm start与 Claude for Desktop 一起使用
打开您的 Claude for Desktop App 配置:
macOS:
~/Library/Application Support/Claude/claude_desktop_config.jsonWindows:
%APPDATA%\Claude\claude_desktop_config.json
添加以下配置:
{
"mcpServers": {
"verge-news": {
"command": "node",
"args": ["/absolute/path/to/verge-news-mcp/build/index.js"]
}
}
}重启 Claude 桌面版
与 Smithery 一起使用
您还可以将此 MCP 服务器与Smithery一起使用,这样您就可以轻松共享和使用 MCP 服务器:
确保您已安装 Smithery:
npm install -g @anthropic-ai/smithery要通过 Smithery 使用此服务器,请运行:
smithery use https://github.com/manimohans/verge-news-mcp安装后,您可以将其与 Claude 或任何其他与 MCP 兼容的应用程序一起使用。
Smithery 配置
此存储库包含 Smithery 所需的配置文件:
Dockerfile:定义如何为 MCP 服务器构建 Docker 容器smithery.yaml:为 Smithery 配置 MCP 服务器,包括其功能
有关 Smithery 配置的更多信息,请参阅Smithery 文档。
可用工具
获取每日新闻
获取过去 24 小时内 The Verge 发布的最新新闻文章。
示例查询:“The Verge 今天有什么新闻?”
获取每周新闻
获取过去 7 天内发布的 The Verge 新闻文章。
示例查询:“显示过去一周的 The Verge 新闻。”
**注意:**此工具会随机选择过去一周的 10 条新闻,每次使用时都会提供多样性。
搜索新闻
搜索包含特定关键字的新闻文章。
参数:
keyword:要搜索的词条days(可选):回顾的天数(默认值:30)
示例查询:“从 The Verge 查找有关 AI 的新闻文章。”
发展
# Run in development mode
npm run dev执照
国际学习中心
Available Tools
3 toolsget-daily-newsB
Get the latest news from The Verge for today
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions fetching 'latest news' but doesn't specify aspects like rate limits, authentication needs, data freshness, or what happens if no news is available today. For a tool with zero annotation coverage, this leaves significant gaps in understanding its operational behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's function without any wasted words. It's front-loaded with the core action and resource, making it easy to parse quickly, which is ideal for conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (0 parameters, no output schema, no annotations), the description is adequate but has clear gaps. It explains what the tool does but lacks details on behavioral traits, output format, or differentiation from siblings. For a basic read operation, it meets the minimum viable standard but doesn't provide full context for optimal agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0 parameters with 100% coverage, meaning no parameters are documented in the schema. The description doesn't add parameter details, but since there are no parameters, a baseline score of 4 is appropriate as there's nothing to compensate for, and the description adequately conveys the tool's purpose without parameter confusion.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get') and resource ('latest news from The Verge for today'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'get-weekly-news' (which presumably covers a different time frame) or 'search-news' (which likely offers search capabilities), so it misses the highest score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides minimal guidance by specifying 'for today', implying usage for current news. However, it doesn't explicitly state when to use this tool versus alternatives like 'get-weekly-news' or 'search-news', nor does it mention any exclusions or prerequisites, leaving the agent with incomplete decision-making context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get-weekly-newsB
Get the latest news from The Verge for the past week
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states what the tool does but lacks behavioral details like whether it returns a list or single item, pagination, rate limits, authentication requirements, or error conditions. 'Get' suggests a read operation, but no safety or performance characteristics are disclosed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, front-loaded with the core action, zero waste. Every word contributes to understanding the tool's function without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no annotations, no output schema, and no parameters, the description is incomplete. It lacks details on return format (e.g., list of articles, metadata), error handling, or any behavioral traits needed for reliable agent use, given the complexity of news retrieval.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0 parameters and 100% schema description coverage, the baseline is 4. The description adds context about the time frame ('past week') and source ('The Verge'), which is meaningful beyond the empty schema, though minimal.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get') and resource ('latest news from The Verge for the past week'), making the purpose understandable. It distinguishes from 'get-daily-news' by specifying weekly scope, but doesn't explicitly differentiate from 'search-news' which might also retrieve news.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives like 'get-daily-news' or 'search-news'. The description implies usage for weekly news from The Verge, but doesn't clarify scenarios where other tools would be more appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search-newsB
Search for news articles from The Verge by keyword
| Name | Required | Description | Default |
|---|---|---|---|
| keyword | Yes | Keyword to search for in news articles | |
| days | No | Number of days to look back (default: 30) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions searching by keyword but lacks details on permissions, rate limits, pagination, or the format of returned articles. For a search tool with zero annotation coverage, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without any unnecessary words. It is appropriately sized and front-loaded, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (2 parameters, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose but lacks details on behavioral traits, usage guidelines, and output format, which are important for a search tool. It meets the minimum viable standard but has clear gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, so the input schema already documents both parameters ('keyword' and 'days') clearly. The description adds no additional meaning beyond what the schema provides, such as examples or constraints, but the baseline score of 3 is appropriate since the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Search') and resource ('news articles from The Verge by keyword'), making it easy to understand what it does. However, it doesn't explicitly differentiate from sibling tools like 'get-daily-news' or 'get-weekly-news', which might also retrieve news articles but with different time-based scopes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'get-daily-news' or 'get-weekly-news', nor does it specify scenarios where keyword-based searching is preferred over time-based retrieval, leaving the agent without clear usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
3 tool updates
v1.0.0- Added
get-daily-news - Added
get-weekly-news - Added
search-news
TDQS
Scored across 3 tools
Each tool has a clearly distinct purpose: get-daily-news retrieves today's news, get-weekly-news covers the past week, and search-news allows keyword-based queries. There is no overlap in functionality, making tool selection straightforward for an agent.
All tool names follow a consistent verb-noun pattern with hyphens (e.g., get-daily-news, get-weekly-news, search-news). The naming is predictable and readable throughout the set.
With 3 tools, the server is well-scoped for its purpose of accessing news from The Verge. Each tool earns its place by covering distinct timeframes and search capabilities, avoiding bloat or thinness.
The tool set covers core news retrieval operations (daily, weekly, and search), but lacks advanced features like filtering by category or date range. However, agents can work around these minor gaps for basic news access.
Maintenance
Related MCP Connectors
News search, article lookup, story coverage and save links for hamir's RSS catalogue
Read, search and organize the RSS feeds you follow in Feeder. Tool calls need Feeder Plus.
1Your curated sources (RSS, YouTube, podcasts, Google News) as context for any AI agent. 26 tools.
Google Trends, Google News, Hacker News, Substack posts and podcasts for research and monitoring.
Related MCP Servers
- AlicenseAqualityDmaintenanceEnables fetching daily news summaries from multiple RSS feeds, with tools to add, remove, and list news sources.46 npm1ISC
- AlicenseAqualityDmaintenanceEnables AI agents to fetch and search news from multiple sources including RSS/Atom feeds, HackerNews, and GDELT global news intelligence without requiring an API key.11165 PyPI4MIT
- AlicenseAqualityCmaintenanceEnables AI to manage RSS subscriptions, fetch and summarize news, and organize results into tools like Notion.96 npm3MIT
- AlicenseNot gradedqualityBmaintenanceEnables AI agents to browse and read curated software-development feeds, fetch any RSS/Atom/RDF feed via URL, and filter items by keywords.22 npmMIT