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the0807

geeknews-mcp-server

by the0807
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

GeekNews MCP Server

このプロジェクトは、 GeekNewsから記事をインポートするModel Context Protocol（MCP）サーバーです。 Pythonとして実装されており、BeautifulSoupを使用してWebスクレイピングを実行します。

機能

tool1

tool2

例

例

ツール(Tools)

  • get_articlesツール：GeekNewsから記事をインポートする機能

    • 記事の種類（top、new、ask、show）と返す記事の数を指定できます。

    • 各回答には、件名、URL、ポイント、作成者、時間、コメント数、ランキング情報が含まれています

  • get_weekly_newsツール：GeekNewsから毎週ニュースを取得する機能

    • 特定の週間ニュースIDを指定したり、最新の週間ニュースを取得したりできます

    • 週刊ニュースのタイトル、番号、ID、コンテンツ、URL、アイテムリストなどの情報を提供

    • 各アイテムにはタイトル、URL、ランキング情報が含まれています

Related MCP server: Mozilla Readability Parser MCP Server

使い方

  • Smitheryを使用したインストール

    🚀 geeknews-mcp-server

  • MCP設定ファイルにサーバー情報を追加する

    {
"mcpServers": {
   "geeknews-mcp-server": {
      "command": "npx",
      "args": [
      "-y",
      "@smithery/cli@latest",
      "run",
      "@the0807/geeknews-mcp-server",
      "--key",
      "smithery에서 발급 받은 키"
      ]
   }
}
}

ローカルインストール方法

  1. Git Clone

    git clone https://github.com/the0807/GeekNews-MCP-Server
cd GeekNews-MCP-Server

  2. uvによる環境設定

    uv sync

  3. 仮想環境の実行

    uv venv
source .venv/bin/activate

  4. MCP Inspectorでサーバーをテストする

    uv run mcp
mcp dev main.py

# 터미널에 나오는 URL(MCP Inspector)로 접속하여 서버 테스트

コード構造

  • src/models.py ：記事情報を格納するデータクラスの定義

  • src/parser.py ：GeekNewsウェブサイトのHTMLを解析して記事情報を抽出する

  • src/client.py ：GeekNewsウェブサイトからデータを取得するHTTPクライアント

  • src/config.py ：設定と定数の定義

  • src/server.py : MCPサーバーの実装

  • main.py : サーバー実行エントリポイント

[!Note]

  • このサーバーはGeekNews WebサイトのHTML構造に依存しています。 Webサイトの構造が変更された場合は、解析ロジックを更新する必要があります。

Available Tools

2 tools
get_articlesA
        GeekNews에서 아티클을 가져오는 도구
        
        Args:
            type: 아티클 유형 (top, new, ask, show)
            limit: 반환할 아티클 수 (최대 30)
        
        Returns:
            List[Dict[str, Any]]: 아티클 목록
            
        Raises:
            ValueError: 유효하지 않은 아티클 유형이 지정된 경우
ParametersJSON Schema
NameRequiredDescriptionDefault
typeNotop
limitNo

TDQS

A3.5/5.0
Behavior3/5

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 the return type (List[Dict[str, Any]]) and raises a ValueError for invalid types, adding some context. However, it doesn't cover important aspects like rate limits, authentication needs, or whether it's read-only/destructive, leaving gaps for a tool with parameters.

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

Conciseness4/5

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

The description is well-structured with sections for Args, Returns, and Raises, making it easy to scan. It's appropriately sized with no redundant sentences. However, the initial purpose statement could be more front-loaded for immediate clarity, though it's still efficient.

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

Completeness3/5

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

Given the tool has 2 parameters, no annotations, and no output schema, the description is moderately complete. It covers parameters and return values adequately but lacks behavioral details like error handling beyond ValueError, performance constraints, or sibling tool differentiation. It's sufficient for basic use but has clear gaps for full contextual understanding.

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

Parameters5/5

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

The description adds significant meaning beyond the input schema, which has 0% description coverage. It explains that 'type' is the article type with valid values (top, new, ask, show) and 'limit' is the number of articles to return with a maximum of 30. This fully compensates for the schema's lack of descriptions, providing clear semantics for both parameters.

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 tool's purpose: 'GeekNews에서 아티클을 가져오는 도구' (Get articles from GeekNews). It specifies the verb '가져오는' (get/fetch) and resource '아티클' (articles), making the action explicit. However, it doesn't distinguish from the sibling tool 'get_weekly_news', which likely serves a different purpose but isn't contrasted here.

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 no guidance on when to use this tool versus alternatives. It mentions parameters and returns but doesn't explain context, prerequisites, or comparisons to 'get_weekly_news'. Usage is implied through parameter details but lacks explicit when/when-not instructions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get_weekly_newsB
        GeekNews에서 주간 뉴스를 가져오는 도구
        
        Args:
            weekly_id: 주간 뉴스 ID (빈 문자열인 경우 가장 최근 주간 뉴스를 가져옴)
            
        Returns:
            Dict[str, Any]: 주간 뉴스 정보
ParametersJSON Schema
NameRequiredDescriptionDefault
weekly_idNo

TDQS

B3.1/5.0
Behavior2/5

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 states the tool fetches weekly news but doesn't describe what '가져오는' entails (e.g., read-only operation, data format, potential errors, or rate limits). For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior and safety profile.

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

Conciseness4/5

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

The description is appropriately sized and front-loaded, with the core purpose stated first in a single sentence. The Args and Returns sections are structured clearly, though the inclusion of type hints like 'Dict[str, Any]' adds minor verbosity without schema support. Overall, it's efficient with minimal waste.

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

Completeness3/5

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

Given the tool's low complexity (1 parameter, no output schema, no annotations), the description is somewhat complete but has gaps. It covers the parameter semantics well but lacks behavioral details and usage guidelines relative to the sibling tool. Without annotations or output schema, more context on what the tool returns or how it behaves would improve completeness.

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

Parameters4/5

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

The description adds meaningful semantics beyond the input schema, which has 0% coverage. It explains that 'weekly_id' is a weekly news ID and specifies that an empty string fetches the most recent weekly news, clarifying the parameter's purpose and default behavior. This compensates well for the lack of schema documentation.

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 tool's purpose: 'GeekNews에서 주간 뉴스를 가져오는 도구' (Get weekly news from GeekNews). It specifies the verb '가져오는' (get/fetch) and the resource '주간 뉴스' (weekly news). However, it doesn't explicitly differentiate from the sibling tool 'get_articles', which might also retrieve news content, leaving some ambiguity about when to use each.

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 no guidance on when to use this tool versus alternatives like 'get_articles'. It mentions that an empty weekly_id fetches the most recent weekly news, which is a usage hint, but lacks explicit context, prerequisites, or exclusions for tool selection.

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. 2 tool updates
    • First observedget_articles
    • First observedget_weekly_news
Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

B3.3/5.0

Scored across 2 tools

Disambiguation5/5

The two tools have clearly distinct purposes: get_articles retrieves articles by type (top, new, ask, show) with a limit parameter, while get_weekly_news fetches weekly news by ID or the most recent one. There is no overlap in functionality or ambiguity between them.

Naming Consistency5/5

Both tools follow a consistent verb_noun naming pattern (get_articles and get_weekly_news), using snake_case throughout. The naming is predictable and readable without any deviations or mixed conventions.

Tool Count2/5

With only 2 tools, the server feels thin and under-scoped for a news domain. While the tools cover basic retrieval, there are likely missing operations (e.g., searching, filtering, or interacting with articles) that would enhance functionality, making the count too low for comprehensive coverage.

Completeness2/5

The tool surface is severely incomplete for a news server. It only provides read operations (get_articles and get_weekly_news) with no support for creating, updating, deleting, or searching articles. This lack of CRUD/lifecycle coverage will limit agent capabilities and cause failures in more complex workflows.

Maintenance

ActivityInactive
ResponsivenessNo issues

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