MCP Web Search Tool

@gabrimatic

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基本情報

カテゴリ

検索

ライセンス

MIT

トランスポート

stdio

作者

gabrimatic

MCP Web Search Tool について

A MCP server providing real-time web search capabilities to any AI model.

#agent #mcp #claude#search-agent#claude-ai#websearch-agent#model-context-protocol #mcp-server

MCP Web Search Tool の設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "mcp-web-search-tool": {
      "command": "docker",
      "args": [
        "build",
        "-t",
        "mcp-web-search",
        "."
      ]
    }
  }
}

MCP Web Search Tool のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is MCP Web Search Tool?

MCP Web Search Tool is an MCP server that lets AI assistants perform live web searches, read full page content, and retrieve source citations. It uses stdio transport, has pluggable providers, and requires no scraper dependencies.

How to use MCP Web Search Tool?

Clone the repository, install dependencies with npm, copy the .env.example file and optionally set BRAVE_API_KEY, then build and start. Docker is also supported. For client integration (Claude Desktop, VS Code, Cursor, etc.), see MCP_CLIENTS.md.

Key features of MCP Web Search Tool

Five tools: web_search, news_search, image_search, fetch_url, list_providers
Search returns ranked summaries with stable IDs and structured JSON
Primary provider is Brave Search; keyless DuckDuckGo fallback for web search
fetch_url strips scripts, styles, nav, footer, and aside from page text
Configurable caching (LRU+TTL) for both search and URL fetch results
Environment‑driven configuration for timeouts, limits, and provider selection

Use cases of MCP Web Search Tool

Get current, source‑backed answers to live questions during a conversation
Research topics by searching and reading full articles with cited sources
Find recent news with source name and publish date via news_search
Retrieve images with thumbnails for visual queries
Integrate real‑time web data into AI assistant workflows without additional scraping tools

よくある質問

What are the runtime requirements?

Node.js >= 20.18 and npm >= 10. The server uses native `fetch` and has no other scraper dependencies.

Do I need a Brave Search API key?

No. Without a key, `web_search` runs on DuckDuckGo as a keyless fallback. However, `news_search` and `image_search` require a Brave key. Set `ALLOW_KEYLESS=false` to refuse startup without a key.

What does `fetch_url` refuse to fetch?

It rejects non‑`http(s)` schemes and any host that resolves to private, loopback, link‑local, multicast, or IPv4‑mapped IPv6 private addresses (see `SECURITY.md`).

Which search providers are available?

Brave Search (default when `BRAVE_API_KEY` is set) and DuckDuckGo (keyless fallback). Call `list_providers` to check availability of news and image search in the current session.

How can I configure caching?

Via environment variables: `CACHE_MAX_ENTRIES` (default 256) and `CACHE_TTL_MS` (default 300 000) for search cache; `FETCH_CACHE_MAX` (default 128) and `FETCH_CACHE_TTL_MS` (default 600 000) for URL fetch cache.

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