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YeonwooSung

metasearch-mcp

by YeonwooSung

元搜索 MCP 服务器

用于元搜索的 MCP 服务器

成分

该服务器使用 Tavily API 根据指定的查询执行搜索。

  • 搜索结果以文本格式返回。

  • 搜索结果包括 AI 响应、URI 和搜索结果的标题。

工具

该服务器实现了以下工具:

  • 搜索:根据指定的查询执行搜索

    • 必需参数:“查询”

    • 可选参数:“search_depth”(基本或高级)

安装

  1. 下载存储库。

git clone https://github.com/YeonwooSung/metasearch-mcp.git
  1. 打开 Claude Desktop 配置文件。

On MacOS: `~/Library/Application\ Support/Claude/claude_desktop_config.json`
On Windows: `C:\Users\[username]\AppData\Roaming\Claude\claude_desktop_config.json`
  1. 编辑配置文件如下:

"mcpServers": {
  "tavily-search": {
    "command": "uv",
    "args": [
      "--directory",
      "C:\\your_path\\mcp-server-tavily",
      "run",
      "tavily-search"
    ],
    "env": {
      "TAVILY_API_KEY": "YOUR_TAVILY_API_KEY",
      "PYTHONIOENCODING": "utf-8"
    }
  }
}
  1. 重新启动 Claude Desktop。

Related MCP server: AIE7-hw13-mcp

用法

在 Claude Desktop 中,当您询问“请搜索某些内容”时,您将收到搜索结果。

搜索示例:

Please search in detail for today's events in Kamakura

响应示例:

According to the search results, the following events start today, December 1st:
"Kamakura Promotion Photo Contest 2025"
Period: December 1, 2024 - January 31, 2025
A photo contest for those who love Kamakura
Applications start accepting from today
Also, as a related upcoming event:
On December 7th, an exhibition by 12 Kamakura artists will be held at the Seibu Press Inn Kamakura Ofuna Station East Exit Lounge.

日志存储位置

日志存储在以下位置:

对于 Windows:

C:\Users\[username]\AppData\Roaming\Claude\logs\mcp-server-tavily-search

使用游标执行

  1. 创建一个 shell 脚本(例如script.sh ),如下所示:

#!/bin/bash
TARGET_DIR=/path/to/mcp-server-tavily
cd "${TARGET_DIR}"
export TAVILY_API_KEY="your-api-key"
export PYTHONIOENCODING=utf-8
uv --directory $PWD run tavily-search
  1. 配置 Cursor 的 MCP 服务器设置如下:

Name: tavily-search
Type: command
Command: /path/to/your/script.sh
  1. 保存设置。

  2. 保存设置后,您可以要求 Cursor 的 Composer-Agent“搜索某些内容”,它将返回搜索结果。

使用 Docker Compose 在本地环境中运行

目的

对于无法使用 Claude Desktop 的 Windows/MacOS 以外的操作系统,本节介绍如何使用 Docker compose 在本地环境中设置和运行 MCP 服务器和客户端。

步骤

  1. 安装 Docker。

  2. 下载存储库。

git clone https://github.com/YeonwooSung/metasearch-mcp.git
  1. 运行 Docker compose。

docker compose up -d
  1. 执行客户端。

docker exec mcp_server uv --directory /usr/src/app/mcp-server-tavily/src run client.py
  1. 执行结果

  2. 如下所示搜索可用工具后,将向 Tavily 发出查询并返回响应

A
license - permissive license
-
quality - not tested
D
maintenance

Maintenance

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