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Web Search MCP Server

@matemiro

リポジトリ

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

基本情報

カテゴリ

検索

ランタイム

python

トランスポート

stdio

公開者

matemiro

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"
      ]
    }
  }
}

ツール

ツールは検出されませんでした

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

FAQ from Web Search MCP Server

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.

What are the runtime requirements?

Python 3.13+, the uv package installer/resolver, and a valid Tavily API key obtained from tavily.com.

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.

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.

How are errors handled?

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

コメント

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