这是与SearXNG集成的MCP SSE模型上下文协议（MCP）服务器实现，为AI代理提供强大且尊重隐私的搜索能力。

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概述

该项目演示了如何构建一个MCP服务器，使AI代理能够利用SearXNG实例进行网页搜索。它作为一个实用模板，用于创建自己的MCP服务器，并以SearXNG为后端。

该实现遵循了Anthropic制定的最佳MCP服务器构建实践，允许与任何兼容MCP的客户端无缝集成。

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先修条件

• Python 3.9+
• 访问正在运行的 SearXNG 实例（本地或远程）
• Docker（可选，用于容器化部署）
• uv（可选，用于快速的Python依赖管理）
• Smithery（可选，用于MCP服务器管理）

SearXNG 服务器（必备）

你必须运行并可访问 SearXNG 服务器。推荐的方法是通过 Docker：

• 这将在端口 32768 上运行 SearXNG，并在 /root/searxng 中保持配置。
• MCP服务器默认期望SearXNG在http://172.17.0.1:32768可用（参见.env）。

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安装

使用紫外线

如果没有 UV，就安装它：

SearXNG MCP Server

An MCP sse implementation of the Model Context Protocol (MCP) server integrated with SearXNG for providing AI agents with powerful, privacy-respecting search capabilities.

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Overview

This project demonstrates how to build an MCP server that enables AI agents to perform web searches using a SearXNG instance. It serves as a practical template for creating your own MCP servers, using SearXNG as a backend.

The implementation follows the best practices laid out by Anthropic for building MCP servers, allowing seamless integration with any MCP-compatible client.

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Prerequisites

• Python 3.9+
• Access to a running SearXNG instance (local or remote)
• Docker (optional, for containerized deployment)
• uv (optional, for fast Python dependency management)
• Smithery (optional, for MCP server management)

SearXNG Server (Required)

You must have a SearXNG server running and accessible. The recommended way is via Docker:

docker run -d --name=searxng -p 32768:8080 -v "/root/searxng:/etc/searxng" \
  -e "BASE_URL=http://0.0.0.0:32768/" \
  -e "INSTANCE_NAME=home" \
  --restart always searxng/searxng

• This will run SearXNG on port 32768 and persist configuration in /root/searxng.
• The MCP server expects SearXNG to be available at http://172.17.0.1:32768 by default (see .env).

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Installation

Using uv

Install uv if you don’t have it:

pip install uv

Clone this repository:

git clone https://github.com/The-AI-Workshops/searxng-mcp-server.git
cd searxng-mcp-server/dev/searXNG-mcp

Install dependencies:

uv pip install -r requirements.txt

Create a .env file based on the provided example:

nano .env
# Edit .env as needed

Configure your environment variables in the .env file (see Configuration section).

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Using Docker (Recommended)

Build the Docker image:

docker build -t mcp/searxng-mcp .

Create a .env file and configure your environment variables.

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Run the Docker image:

docker run -d --env-file ./.env -p 32769:32769 mcp/searxng-mcp

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Using Smithery

Smithery is a command-line tool for managing AI agent tools and MCP servers.

Install Smithery if you don’t have it (see Smithery documentation for various installation methods, e.g., using pipx):

pipx install smithery

Install the SearXNG MCP server using Smithery:

smithery install @The-AI-Workshops/searxng-mcp-server

This will install the server and its dependencies into a dedicated environment managed by Smithery.