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serper-search-scrape-mcp-server

by marcopesani
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TypeScript
Remote

Serper検索とスクレイピングMCPサーバー

鍛冶屋のバッジ

Serper APIを使用したWeb検索およびWebページスクレイピング機能を提供するTypeScriptベースのMCPサーバーです。このサーバーはClaude Desktopと統合されており、強力なWeb検索機能とコンテンツ抽出機能を実現します。

特徴

ツール

  • google_search - Serper API 経由でウェブ検索を実行する

    • オーガニック検索結果、ナレッジグラフ、「他のユーザーも質問しています」、関連検索など、豊富な検索結果

    • 地域と言語のターゲティングをサポート

    • 場所、ページネーション、時間フィルター、自動修正のオプションパラメータ

    • 高度な検索演算子をサポートします:

      • site : 結果を特定のドメインに限定する

      • filetype : 特定のファイルタイプに制限します（例: 'pdf'、'doc'）

      • inurl : URLに単語を含むページを検索

      • intitle : タイトルに単語が含まれるページを検索

      • related ：類似のウェブサイトを探す

      • cache : 特定の URL の Google のキャッシュ バージョンを表示します

      • before : YYYY-MM-DD形式の以前の日付

      • after : YYYY-MM-DD形式の日付

      • exact : 完全なフレーズ一致

      • exclude : 検索結果から除外する用語

      • or : 代替用語（OR演算子）

  • scrape - Webページからコンテンツを抽出する

    • プレーンテキストとオプションのマークダウンコンテンツを取得する

    • JSON-LDとヘッドメタデータを含む

    • 文書構造を保持

Related MCP server: go_serper_mcp_server

要件

  • Node.js >= 18

  • Serper API キー ( SERPER_API_KEY環境変数として設定)

発達

依存関係をインストールします:

npm install

サーバーを構築します。

npm run build

自動リビルドを使用した開発の場合:

npm run watch

テストを実行します:

npm test                  # Run all tests
npm run test:watch       # Run tests in watch mode
npm run test:coverage    # Run tests with coverage
npm run test:integration # Run integration tests

環境変数

ルート ディレクトリに.envファイルを作成します。

SERPER_API_KEY=your_api_key_here

デバッグ

MCPサーバーはstdio経由で通信するため、デバッグが困難になる場合があります。パッケージスクリプトとして提供されているMCP Inspectorの使用をお勧めします。

npm run inspector

インスペクターは、ブラウザでデバッグ ツールにアクセスするための URL を提供します。

インストール

Smithery経由でインストール

Smithery経由で Claude Desktop に Serper Search and Scrape を自動的にインストールするには:

npx -y @smithery/cli install @marcopesani/mcp-server-serper --client claude

クロードデスクトップ

次の場所にサーバー設定を追加します:

  • MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json

  • Windows: %APPDATA%/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "serper-search": {
      "command": "npx",
      "args": ["-y", "serper-search-scrape-mcp-server"],
      "env": {
        "SERPER_API_KEY": "your_api_key_here"
      }
    }
  }
}

クライン

  1. Cline拡張機能の設定を開く

  2. 「MCPサーバー」タブを開く

  3. 「MCPサーバーの構成」をクリックします

  4. サーバー設定を追加します:

{
  "mcpServers": {
    "github.com/marcopesani/mcp-server-serper": {
      "command": "npx",
      "args": ["-y", "serper-search-scrape-mcp-server"],
      "env": {
        "SERPER_API_KEY": "your_api_key_here"
      },
      "disabled": false,
      "autoApprove": ["google_search", "scrape"]
    }
  }
}

追加のCline構成オプション:

  • disabled : サーバーを有効にするにはfalseに設定します

  • autoApprove : 使用ごとに明示的な承認を必要としないツールのリスト

カーソル

  1. カーソル設定を開く

  2. 「機能」設定を開く

  3. 「MCPサーバー」セクションで、「新しいMCPサーバーを追加」をクリックします。

  4. 名前を選択し、「タイプ」として「コマンド」を選択します

  5. 「コマンド」フィールドに次のように入力します。

env SERPER_API_KEY=your_api_key_here npx -y serper-search-scrape-mcp-server

ドッカー

Dockerを使ってサーバーを実行することもできます。まずはイメージをビルドします。

docker build -t mcp-server-serper .

次に、Serper API キーを使用してコンテナを実行します。

docker run -e SERPER_API_KEY=your_api_key_here mcp-server-serper

あるいは、環境変数が.envファイルにある場合は、次のようにします。

docker run --env-file .env mcp-server-serper

開発の場合、ソース コードをボリュームとしてマウントする必要がある場合があります。

docker run -v $(pwd):/app --env-file .env mcp-server-serper

注意: your_api_key_here実際の Serper API キーに置き換えてください。

Available Tools

2 tools
scrapeC

Tool to scrape a webpage and retrieve the text and, optionally, the markdown content. It will retrieve also the JSON-LD metadata and the head metadata.

ParametersJSON Schema
NameRequiredDescriptionDefault
urlYesThe URL of the webpage to scrape.
includeMarkdownNoWhether to include markdown content.

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 states what the tool retrieves (text, markdown, JSON-LD, head metadata) but lacks critical behavioral details such as rate limits, authentication needs, error handling, or whether it performs destructive actions (e.g., modifying data). For a web scraping tool with no 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.

Conciseness4/5

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

The description is concise and front-loaded in a single sentence, efficiently stating the core functionality without unnecessary details. Every part earns its place, though it could be slightly more structured (e.g., separating outputs). It avoids redundancy and is appropriately sized for the tool's complexity.

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 moderate complexity (web scraping with two parameters), no annotations, and no output schema, the description is partially complete. It covers what the tool retrieves but misses behavioral aspects like rate limits or error handling. Without an output schema, it should ideally describe return values more explicitly, but it does list the types of content retrieved, providing some context.

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?

The input schema has 100% description coverage, clearly documenting both parameters ('url' and 'includeMarkdown'). The description adds no additional meaning beyond the schema—it doesn't explain parameter interactions, constraints, or usage examples. With high schema coverage, the baseline score of 3 is appropriate as the schema handles the heavy lifting.

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: 'scrape a webpage and retrieve the text and, optionally, the markdown content. It will retrieve also the JSON-LD metadata and the head metadata.' This specifies the verb (scrape), resource (webpage), and outputs (text, markdown, JSON-LD, head metadata). However, it doesn't explicitly differentiate from the sibling tool 'google_search', which likely serves a different purpose (searching vs. scraping).

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 doesn't mention the sibling tool 'google_search' or any other scraping-related tools, nor does it specify prerequisites, contexts, or exclusions for usage. This leaves the agent without clear direction on 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 updatesv1.0.0
    • First observedgoogle_search
    • First observedscrape
Deploy Server
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TDQS

B3.3/5.0

Scored across 2 tools

Disambiguation5/5

The two tools have clearly distinct purposes: google_search is for performing web searches and retrieving search results, while scrape is for extracting content from a specific webpage. There is no overlap in functionality, making it easy for an agent to choose the right tool for each task.

Naming Consistency5/5

Both tools follow a consistent naming pattern using snake_case with descriptive, action-oriented names (google_search and scrape). The naming is straightforward and predictable, with no deviations or mixed conventions.

Tool Count3/5

With only 2 tools, the server feels thin for a search-and-scrape domain, as it might lack additional utilities like batch processing, advanced filtering, or result summarization. However, the core functions are covered, making it borderline but functional.

Completeness4/5

The tools cover the essential workflows for search and scraping: performing searches and extracting webpage content. Minor gaps exist, such as no tool for managing search history or handling pagination, but agents can work around these with the provided tools.

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources

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