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Web Search MCP Server

@matemiro

基本情報

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トランスポート

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作者

matemiro

Web Search MCP Server について

A Model Context Protocol (MCP) server that provides a web search tool using the Tavily API. This server enables AI models to search the internet and retrieve up-to-date information.

#mcp#mcp-server#tavily-search

Web Search MCP Server 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-Tavily-Web-Search-Server": {
      "command": "uv",
      "args": [
        "venv"
      ]
    }
  }
}

Web Search MCP Server 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 Web Search MCP Server?

Web Search MCP Server is a Model Context Protocol (MCP) server that provides a web search tool using the Tavily API. It acts as a bridge between AI models and the Tavily search engine, enabling models to search the internet and retrieve up-to-date information during conversations.

How to use Web Search MCP Server?

Install Python 3.13+ and uv, then clone the repository, set up a virtual environment, and install dependencies with uv pip sync. Create a .env file from the provided template and add your Tavily API key. Run the server with uv run web_search_server.py. The server uses the stdio transport method for MCP communication.

Key features of Web Search MCP Server

  • Real-time web search via Tavily API
  • Customizable search topic (general, news, finance)
  • Adjustable search depth (basic, advanced)
  • Maximum results and time range filtering (day, week, month, year)
  • Domain inclusion and exclusion lists

Use cases of Web Search MCP Server

  • AI assistants retrieving current internet information during conversations
  • Chatbots answering queries that require real-time data
  • Research agents gathering up-to-date results from specified domains
  • News or finance searches filtered by recent time ranges

よくある質問

1

What exactly does this server do?

It exposes a single tool (`search_web_tool`) that lets AI models search the web via the Tavily API and return a list of results containing title, URL, content, and relevance score.

2

What are the runtime requirements?

Python 3.13+, the `uv` package installer/resolver, and a valid Tavily API key obtained from [tavily.com](https://tavily.com/).

3

How do I configure the Tavily API key?

Copy the `env-sample` file to `.env`, then edit `.env` to set `TAVILY_API_KEY=your-api-key-here`.

4

What parameters does the search tool accept?

It requires a `query` string and accepts optional parameters: `search_topic`, `search_depth`, `max_results`, `time_range`, `include_domains`, and `exclude_domains`.

5

How are errors handled?

If an error occurs during a search operation, the tool returns an error message describing the issue.

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