MCP server for SearXNG integration
MCP Searxng connects MCP Searxng to AI assistants that speak the Model Context Protocol. MCP server for SearXNG integration.
An MCP server that integrates the SearXNG API, giving AI assistants web search capabilities.
searxng_web_search — Execute web searches with paginationsearxng_search_suggestions — Get autocomplete suggestions for refining search queriessearxng_instance_info — Discover categories aggregated from reachable configured SearXNG instances, optionally include engine names, and inspect defaults, locales, and plugins from the primary reachable instance. Categories—and engines when reqweb_url_read — Read URL content as markdown with content-type-aware handling and advanced extraction optionsCompare MCP servers by category, or browse hosted MCP servers if you prefer an endpoint over a local process.
Check the linked publisher documentation and your connected client's tool list. Names and availability can vary with the server version and account permissions.
| Tool | What it does |
|---|---|
| searxng_web_search | Find sources and refine results |
| searxng_search_suggestions | Complete or refine a query |
| searxng_instance_info | Inspect categories, engines and defaults |
| web_url_read | Read a known URL as text/Markdown |
{
"mcpServers": {
"searxng": {
"command": "npx",
"args": [
"-y",
"mcp-searxng"
],
"env": {
"SEARXNG_URL": "https://search.example.com"
}
}
}
}From the project documentation. Replace placeholders and example paths before connecting.
| Variable | Description | Required |
|---|---|---|
| SEARXNG_URL | Declared in the maintainer’s client configuration. | Yes |
Retrieve public web pages as readable Markdown with the reference Fetch MCP server, including pagination for longer responses.
Use Firecrawl MCP to retrieve website content and extract information for research through Firecrawl’s API-backed web tools.
The original Chromium automation reference server — simple, screenshot-driven browser control.
Puppeteer-powered browser control that drives pages from the accessibility tree instead of pixels.
Automates browsers and APIs, enabling Large Language Models (LLMs) to interact with web pages for tasks like screenshot capture and JavaScript
Search built for AI, not humans — semantic web search that returns model-ready content, plus code context.