Searxng MCP Server
This is an MCP server implementation project based on SearXNG, providing privacy - protected search capabilities for AI agents. The project is deployed through Docker containerization, supports two transport protocols, SSE and Stdio, and can be easily integrated into MCP - compatible clients.
rating : 2.5 points
downloads : 16
What is the SearXNG MCP Server?
This is a server based on the Model Context Protocol (MCP), specifically designed to provide privacy - protected web search functionality for AI agents. It uses the open - source SearXNG search engine as the backend, allowing AI assistants to perform web queries securely without revealing user privacy.How to use the SearXNG MCP Server?
You can connect the server to MCP - compatible AI clients (such as Claude Desktop or Windsurf) through simple configuration. The server supports two connection methods: SSE (Server - Sent Events) and Stdio (Standard Input/Output).Use cases
Suitable for scenarios where AI assistants are required for web searches but privacy protection is emphasized, such as personal knowledge management, research assistance, information verification, etc. It is particularly suitable for replacing traditional search engine APIs in privacy - sensitive environments.Main features
Privacy - protected searchProvide a privacy - protected search service that does not track users or record queries through SearXNG
MCP protocol integrationFully compatible with the Model Context Protocol and can be seamlessly integrated with various MCP clients
Multiple transport protocolsSupport two communication methods, SSE and Stdio, to adapt to different deployment environments
Docker containerizationProvide a Docker image to simplify the deployment and management process
Advantages and limitations
Advantages
Protect user privacy and do not record search queries
Open - source and self - hosted, with full control over data flow
Support multiple search parameters and filtering conditions
Lightweight and easy to deploy
Limitations
Need to maintain the SearXNG instance by yourself
The search speed may be slightly slower than that of commercial search engine APIs
Some advanced search functions may be restricted
How to use
Set up the SearXNG server
First, you need to run a SearXNG instance, which can be quickly deployed using Docker
Deploy the MCP server
You can choose to use Docker or directly run the Python script
Configure the MCP client
Add the MCP server configuration to your AI client and select the SSE or Stdio connection method
Usage examples
Academic research assistanceThe AI assistant searches for the latest academic papers and research results through the MCP server
Fact - checkingVerify the accuracy of specific facts or data
Frequently Asked Questions
Why choose SearXNG instead of directly using the Google or Bing API?
How to improve the accuracy of search results?
What search parameters does the server support?
Related resources
SearXNG official documentation
The official documentation of the SearXNG search engine
Model Context Protocol specification
The official specification document of the MCP protocol
GitHub repository
Project source code
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