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.