SearxNG MCP Server

Overview

The SearxNG Simple MCP Server bridges the gap between privacy‑respecting web search and AI assistants that follow the Model Context Protocol (MCP). By exposing a lightweight MCP interface to a SearxNG instance, the server lets large language models (LLMs) retrieve up-to‑date information from the internet without sacrificing user privacy or consuming excessive context space. This is particularly valuable for developers who need real‑time data while maintaining strict compliance with privacy policies.

The server’s core function is to translate MCP search requests into HTTP queries against a configured SearxNG endpoint, then return the results in a format that is easy for an LLM to ingest. It limits the amount of data sent back by default, focusing on concise, well‑structured results that preserve valuable token budget for the assistant’s reasoning. Because SearxNG aggregates results from multiple search engines without tracking, the MCP server inherits this privacy‑first stance, making it an ideal choice for sensitive or regulated use cases.

Key capabilities include:

• Privacy‑focused search: No user data is stored or forwarded to third parties; all queries are routed directly through the chosen SearxNG instance.
• Minimal context footprint: The server returns only the essentials—titles, URLs, and snippets—so the assistant can quickly decide what to use without bloating the conversation.
• Configurable parameters: Environment variables let developers set result counts, language filters, timeouts, and output formats (plain text or JSON) to match their workflow.
• MCP compatibility: The server speaks the same protocol used by Claude Desktop and other MCP‑compliant clients, enabling seamless integration without custom adapters.

In practice, developers can embed the server into a Claude‑powered chatbot that answers user questions with up‑to‑date facts, pulls the latest news headlines for a newsroom assistant, or fetches product specifications for an e‑commerce support bot—all while keeping the search engine out of the LLM’s context window. The server can be launched via Docker, pipx, uvx, or a simple Python command, offering flexibility across development and production environments.

Because the MCP server is intentionally lightweight, it adds negligible latency to search operations while preserving the LLM’s token budget. This combination of privacy, efficiency, and ease of integration makes the SearxNG Simple MCP Server a standout solution for developers who need reliable, real‑time web search within their AI workflows.