Web Search MCP server

websearch-skill

Open-source multi-engine web search and content extraction for AI agents. Internal layers communicate through versioned JSON Schema contracts.

Status: early. First public release 2026-06-22; current version in CHANGELOG.md. Available now: keyless search, Markdown extraction, five agent commands, self-hosted SearXNG, and a NordVPN egress proxy that two env vars enable and lock. These are covered by the test suite. There is no MCP server; use the CLI directly or install the skill (see No MCP below). Hard anti-bot tiers and local reranking remain on the roadmap. Pin a version and test it in a sandbox before using it with sensitive data.

What it is

A self-hosted web search and page reader for AI agents, with no API keys or paid search service. It queries multiple engines, combines and deduplicates the results, then fetches pages as clean Markdown. The CLI runs locally and sends queries directly to the configured engines.

Core commands:

• init reads the settings files, starts local SearXNG (and Tor, when that layer is on), and reports available capabilities.
• websearch** finds pages: ranked, deduplicated results across engines, each with a reusable handle.
• webfetch** reads a page: clean Markdown, fenced as untrusted, paginated so a long page never overflows context.
• webopen** pages back through a document you already fetched, from cache, without hitting the network again.

Additional keyless commands:

• arxiv searches arXiv papers and returns structured metadata (authors, abstract, categories, abstract and PDF links).
• github searches GitHub repositories and returns typed fields you can sort on (stars, language, topics).
• tor starts a local Tor and routes everything through it, which is what makes .onion reachable and --onion search the Tor indexes. Off by default; see Tor below.

One runtime, one call

The whole toolkit is one Python package with one CLI, websearch. There is no Node service, no npm runtime, no daemon of its own, and nothing to compose; the only requirement is uv, which fetches a compatible Python on its own. The npx skills add line under Install copies skill folders into agents once; nothing from Node runs afterwards.

An agent brings everything online with one call:

websearch init

init reads the settings files, starts the local SearXNG when it is not already running, starts Tor when that layer is on, runs the self-test, and reports capabilities and next actions. There is nothing to probe first and no order to follow: the same call is correct on a fresh machine and on one where everything is already up.

SearXNG is an optional extra engine catalog that the toolkit operates for you: init (or websearch searxng up) clones it, installs it into its own virtualenv, and runs it as a detached local Python process. Docker is never required; docker/searxng/ exists only as an alternative for hosts that prefer a container.

Engines, out of the box, no keys

The default engine is the keyless ddgs metasearch library, which spans Google, Brave, DuckDuckGo, Yandex, Yahoo, Startpage, Mojeek, Wikipedia, and Grokipedia. Each query uses the providers that respond. The agent-facing web-search command requires no account, service, or engine flags. The lower-level search command can restrict providers with --ddgs-backends google,brave,mojeek. Provider availability varies by network; websearch doctor reports it per provider.

Shortened. The full README is on GitHub.