iflow-mcp_the-ai-workshops-searxng-mcp-server

# SearXNG MCP Server An MCP sse implementation of the Model Context Protocol (MCP) server integrated with [SearXNG](https://github.com/searxng/searxng) for providing AI agents with powerful, privacy-respecting search capabilities. --- ## 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. --- ## Prerequisites - Python 3.9+ - Access to a running SearXNG instance (local or remote) - Docker (optional, for containerized deployment) - [uv](https://github.com/astral-sh/uv) (optional, for fast Python dependency management) - [Smithery](https://github.com/The-AI-Workshops/smithery) (optional, for MCP server management) ### SearXNG Server (Required) You must have a SearXNG server running and accessible. The recommended way is via Docker: ```bash 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`). --- ## Installation ### Using uv Install uv if you don't have it: ```bash pip install uv ``` Clone this repository: ```bash git clone https://github.com/The-AI-Workshops/searxng-mcp-server.git cd searxng-mcp-server/dev/searXNG-mcp ``` Install dependencies: ```bash uv pip install -r requirements.txt ``` Create a `.env` file based on the provided example: ```bash nano .env # Edit .env as needed ``` Configure your environment variables in the `.env` file (see Configuration section). --- ### Using Docker (Recommended)…