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NYTimes Article Search MCP Server

by angheljf

NYTimes 기사 검색 MCP 서버

대장간 배지

이는 키워드를 기반으로 최근 30일간의 뉴욕 타임스 기사를 검색할 수 있는 TypeScript 기반 MCP 서버입니다. 다음을 제공하여 핵심 MCP 개념을 보여줍니다.

  • 기사 검색 도구

  • New York Times API와의 통합

NYTimes 기사 검색

특징

도구

  • search_articles - 키워드를 기준으로 지난 30일간의 NYTimes 기사 검색

    • keyword 필수 매개변수로 사용합니다.

    • 제목, 초록, URL, 게시 날짜 및 저자가 포함된 기사 목록을 반환합니다.

Related MCP server: image-reader MCP Server

개발

종속성 설치:

지엑스피1

서버를 빌드하세요:

npm run build

자동 재빌드를 사용한 개발의 경우:

npm run watch

디버깅

MCP 서버는 stdio를 통해 통신하므로 디버깅이 어려울 수 있습니다. 패키지 스크립트로 제공되는 MCP Inspector를 사용하는 것이 좋습니다.

npm run inspector

검사기는 브라우저에서 디버깅 도구에 액세스할 수 있는 URL을 제공합니다.

설치

Smithery를 통해 설치

Smithery를 통해 Claude Desktop에 NYTimes Article Search를 자동으로 설치하려면:

npx -y @smithery/cli install nyt --client claude

수동 설치

Claude Desktop과 함께 사용하려면 서버 구성을 추가하세요.

MacOS의 경우: ~/Library/Application Support/Claude/claude_desktop_config.json Windows의 경우: %APPDATA%/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "nyt": {
      "command": "node",
      "args": ["path/to/your/build/index.js"],
      "env": {
        "NYTIMES_API_KEY": "your_api_key_here"
      }
    }
  }
}

환경 변수

프로젝트 루트에 .env 파일을 만들고 New York Times API 키를 추가하세요.

NYTIMES_API_KEY=your_api_key_here

서버 실행

프로젝트를 빌드한 후 다음을 사용하여 서버를 실행할 수 있습니다.

node build/index.js

서버가 시작되어 stdio를 통해 MCP 요청을 수신합니다.

특허

이 프로젝트는 MIT 라이선스에 따라 라이선스가 부여되었습니다.

Available Tools

1 tool
search_articlesC

Search NYTimes articles from the last 30 days based on a keyword

ParametersJSON Schema
NameRequiredDescriptionDefault
keywordYesKeyword to search for in articles

TDQS

C2.9/5.0
Behavior2/5

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 the 30-day time constraint, which is useful, but fails to describe critical behaviors such as response format, pagination, error handling, or any rate limits. For a search tool with zero annotation coverage, this leaves significant gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the core functionality without unnecessary words. Every part ('Search NYTimes articles from the last 30 days based on a keyword') contributes directly to understanding the tool's purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of annotations and output schema, the description is incomplete. It covers the basic purpose and time constraint but omits details on behavioral traits, response structure, and usage guidelines. For a search tool, this leaves the agent with insufficient context to use it effectively.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, with the parameter 'keyword' well-documented in the schema. The description adds minimal value by implying keyword-based filtering but doesn't provide additional semantics like search syntax or examples. Baseline 3 is appropriate when the schema handles parameter documentation effectively.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Search NYTimes articles') and resource ('articles'), specifying the scope ('from the last 30 days') and filtering criteria ('based on a keyword'). It lacks sibling tool differentiation, but since there are no sibling tools, this doesn't reduce clarity.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides basic context (searching recent articles by keyword) but offers no explicit guidance on when to use this tool versus alternatives, prerequisites, or exclusions. Without siblings, the need for differentiation is lower, but it still lacks usage context like rate limits or authentication needs.

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.

  1. 1 tool updatev1.0.0
    • First observedsearch_articles

TDQS

B3.1/5.0

Scored across 1 tool

Disambiguation5/5

With only one tool, there is no possibility of ambiguity or overlap between tools. The single tool 'search_articles' has a clearly defined and distinct purpose.

Naming Consistency5/5

The single tool name follows a clear verb_noun pattern ('search_articles'), and with only one tool, there is no inconsistency to evaluate. The naming is straightforward and appropriate.

Tool Count2/5

One tool is too few for a server with the apparent scope of 'NYTimes Article Search,' which suggests a domain that could benefit from additional operations like filtering by date, retrieving article details, or accessing different sections. A single search tool feels thin and limits functionality.

Completeness2/5

The tool surface is severely incomplete for the domain. While search is a core function, there are obvious gaps such as the inability to retrieve full article content, filter beyond keywords, or access other NYTimes data like sections or authors. This will likely cause agent failures when more comprehensive interactions are needed.

Maintenance

ActivityInactive
ResponsivenessNo issues

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