LibreAI / Dev Tools / wigolo
// devtools · KnockOutEZ/wigolo

wigolo

Local-first web search, fetch, crawl and research for AI coding agents over MCP — no API keys.

★ 5.5k stars⑂ 446 forksAGPL-3.0updated 2026-10
▦ visual — this project's README ships no embeddable screenshot,
so here's a placeholder. The guide below is complete regardless.
// project facts

Project facts

wigolo is an open-source dev tools project by KnockOutEZ (KnockOutEZ/wigolo on GitHub). It has 5,450 GitHub stars and 446 forks, is released under the AGPL-3.0 license, and was last updated on GitHub on 8 October 2026.

GitHub stars
5,450
Forks
446
License
AGPL-3.0
Last updated on GitHub
8 October 2026
Category
Dev Tools
Listing
Full install guide
Official site
Official site
// how it works

How it works

  1. Clarify your agent's web gap

    If your coding agent cannot search or read the web without a paid search API, wigolo is the local replacement.

  2. Initialize the engine

    Run the one-command init, optionally wiring your day-to-day agents (Claude Code, Cursor) in the same step.

  3. Check the setup

    Run wigolo doctor to verify the local engine, cache and agent wiring.

  4. Search from your agent

    Ask your agent a question that needs the web and let it use wigolo's search and fetch tools over MCP.

// features

Why people love it

Multi-engine search

Web search across 18 direct adapters with rank fusion, ML reranking and an explainable per-result score; query arrays search in parallel.

Tiered fetching and crawling

Fetch escalates through tiers — up to a real browser — based on observable signals like SPA markers and challenge pages, and learns per domain.

Ten-tool surface

Beyond search and fetch it includes caching, find-similar, research and agent tools, exposed over MCP, a REST API (POST /v1/{tool}) and SDKs.

Local-first and keyless

Runs on your machine with no API keys and no per-query cost; optional LLM use is opt-in, capped per request, and verified against sources.

Framework integrations

Drop the tools into LangChain, CrewAI or LlamaIndex with dedicated packages, or use the TypeScript/Python SDKs with embedded local mode.

Quality signals

Weak results are flagged as junk, failed engines are reported and stale cache is labeled, so the agent knows what it is standing on.

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// run it

Run it yourself

  1. Clone the repository

    Clone wigolo if you want the source; most users run it via npx.

    git clone https://github.com/KnockOutEZ/wigolo.git
    cd wigolo
  2. Initialize the local engine

    Set up wigolo and wire it into your agents in one command.

    npx wigolo init --agents=claude-code,cursor
  3. Verify the installation

    Run the built-in diagnostics, then ask your agent a web question.

    npx wigolo doctor
// use cases

What you can build

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// faq

Questions, answered

Who maintains wigolo?

wigolo is maintained by KnockOutEZ and contributors; the product site is wigolo.app.

Is wigolo free?

It is open source (AGPL-3.0 per the project's license badge) and free to run locally — its pitch is $0 per query with no search-API subscription.

Does it need a paid API key?

No API keys are required for search and fetch. An optional LLM provider (for example Gemini) can be configured via environment variables for the features that use one.

How does it compare to Tavily or Exa?

Those are hosted, per-query paid APIs; wigolo runs the search/fetch/crawl stack locally on your machine and serves your agents over MCP at no per-query cost.

How do I get started?

Run npx wigolo init, then npx wigolo doctor, and ask your wired-up agent a question that needs the web.

// keep exploring

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// alternatives

Alternatives in Dev Tools

The most-starred other Dev Tools projects in the LibreAI catalogue — the realistic shortlist if wigolo is not the right fit.

Get wigolo

Free and open — grab the source, star the repo, and start creating.