The go-to web for your AI coding agent — local-first search, fetch, crawl & research over MCP. No API keys, no cloud, $0/query. Public beta.
The go-to web for your AI coding agent — local-first search, fetch, crawl & research over MCP. No API keys, no cloud, $0/query. Public beta.
wigolo gives an AI agent one surface for everything web-related: search, fetch, crawl, extract, cache, find-similar, research, and autonomous gather loops. It runs wherever your agent runs — as an MCP server next to your coding agent, as a REST/MCP endpoint on the box where your self-hosted agents live, or embedded through an SDK inside your own app. The core tools need no API keys, nothing it touches leaves ~/.wigolo/, and no bill grows with how much your agent thinks.
npx wigolo init # set up the local engine — any system
npx wigolo init --agents=claude-code,cursor # …or set up + wire your day-to-day agents in one command
Requires Node ≥ 20 and ~1.5 GB of free disk on macOS, Linux, or Windows. Bare init sets up the local engine: it downloads the browser engine and on-device models, runs a health check, and reports each component. Adding --agents wires the named agents in the same run, so a coding agent you use daily is ready in one command.
--agents takes any of claude-code · cursor · codex · gemini-cli · opencode · vscode · windsurf · zed · antigravity (comma-separated); wigolo writes the MCP config and, where supported, instructions for each.npx -y wigolo in its own MCP config. The installation guide has the exact config block for every client, plus Docker, Homebrew, and single-file-binary channels.--interactive is a plain-text flow; --wizard is the full terminal TUI.--no-warmup waits until first use. A failed component download never fails setup; init reports what's not ready with the exact fix and still completes.init is unattended by default, so it's safe in scripts and CI, and any setup problem surfaces right here in the per-component report, before your agent's first call. Search, fetch, crawl, extract, cache, and find-similar work with no API key. Check it's healthy anytime:
npx wigolo doctor
To remove everything cleanly, run npx wigolo config --uninstall --yes. You can also paste the installation guide into any AI assistant and let it do the setup; it's written to be self-contained.
research & agentSearch, fetch, crawl, extract, cache, and find-similar are fully keyless. research, agent, and search format=answer use an LLM to write the synthesized, cited answer. Without one they hand back a raw brief and evidence for your agent to assemble. A free Gemini key turns that into a finished answer:
export WIGOLO_LLM_PROVIDER=gemini
export GEMINI_API_KEY=<free-key> # grab one at aistudio.google.com/apikey — the free tier is plenty
Any provider works (anthropic · openai · groq), or stay fully local and keyless with WIGOLO_LLM_PROVIDER=ollama (or any OpenAI-compatible URL). Set it in your shell or your agent's MCP env block. Providers, models, and the keyless local-model ladder are in the configuration guide.
Every search result is evidence the agent can act on. It carries a verbatim excerpt pinned to its exact position in the source, a citation ID the agent can quote, and a score it can inspect (abridged real shape):
{
"results": [{
"title": "Logical replication - PostgreSQL docs",
"url": "https://www.postgresql.org/docs/current/logical-replication.html",
"excerpt": "Logical replication is a method of replicating data objects…",
"citation_id": "src-1",
"source_span": { "start": 1042, "end": 1305 }, // byte-exact provenance
"evidence_score": { "final": 0.86, "semantic": 0.91, "lexical": 0.78, "engine_consensus": 3 }
}],
"citations": [{ "id": "src-1", "url": "…" }],
"freshness_signal": { "published": "2026-05-12", "confidence": "high" }
}
Weak results get flagged as junk by wigolo's own scorer. Failed engines are reported and stale cache is labeled, so the agent always knows what it's standing on. Full response contracts per tool are in the tools reference.
| Tool | What it does |
|---|---|
search |
Multi-engine web search (18 direct adapters) with rank fusion, ML reranking, and an explainable per-result score. Pass a query array for parallel breadth. Scope by domain and time range, match an exact phrase, or return image results. |
fetch |
Load one URL through a tiered router that auto-escalates from plain HTTP to a headless browser engine on anti-bot challenges or SPA shells. Clean markdown + metadata + links. Handles PDFs, a single-heading section, authenticated sessions, and page actions (click / type / scroll / screenshot). |
️ crawl |
Multi-page crawl — BFS, DFS, sitemap, or map-only. Per-domain rate limits, robots.txt respect, boilerplate dedup. |
extract |
Structured data from a page: tables, metadata, JSON-LD, brand identity, named schemas (Article / Recipe / Product / …), or any custom JSON Schema. |
cache |
Query everything already seen — keyword or hybrid semantic. Plus stats, clear, and change detection. |
find_similar |
Pages similar to a URL or a concept, via 3-way fusion of keyword + semantic + live web. |
research |
Decompose a question → fan out sub-queries → fetch sources → synthesize a cited report (or a structured brief the host LLM writes from). |
agent |
Autonomous gather loop: plan → search → fetch → extract → synthesize, with a step log, time budget, and optional output schema. |
diff + ⏱️ watch |
See exactly what changed on a page since last visit; re-check on demand and deliver changes to a webhook. |
Every tool also runs from the terminal (wigolo search "…" --json), from an interactive shell with NDJSON piping (wigolo shell), over REST, and through the SDKs — CLI reference. Per-tool guides with the full parameter set are in docs/tools.md; runnable examples are in examples/.
wigolo isn't a free stand-in for the paid tools — it's built to match them. It's a focused web layer for your agents: an MCP and REST surface they call directly, with the search and extraction quality the paid services charge for. What separates it:
blocked_by_challenge failure, not a challenge shell returned as content.~/.wigolo/. Nothing reaches a third party unless you explicitly opt into an LLM for synthesis.Here's what one real result looks like, dissected. It includes the failed engine and the weak result, because those are part of the answer too:
Thank you to the sponsors below, who help keep wigolo maintained and free for everyone to use. Their support goes straight into the work.
wigolo is free for all and is meant to stay that way. If you or your company would like to help keep it maintained, there's room for more sponsors — reach out at [email protected], or see SPONSORS.md for the terms. A one-off via Buy Me a Coffee is welcome too.
All four tools converged on the same core answer, and only one of them handed back verbatim, byte-pinned evidence while doing it.
One cold query ran live inside a single Claude Fable 5 session, fanned out to four web tools on equal footing (built-in WebSearch, wigolo, Tavily, Exa), and was judged by the agent on the evidence alone. All four converged on the same answer and the same top source, so the parity is demonstrated on-screen. wigolo alone returned verbatim excerpts pinned to byte-offset source spans, an explainable score decomposition, and live per-engine telemetry, and its own scorer flagged two weak results as junk. The cloud tools earn their place too: Exa rendered the official docs' comparison matrix in full. Run your own query and you'll see the same shape.
| wigolo | Firecrawl | Exa | Tavily | |
|---|---|---|---|---|
| Multi-engine web search | ✅ | ✅ | ✅ | ✅ |
| Fetch & structured extraction | ✅ | ✅ | ✅ | ✅ |
| Whole-site crawl & map | ✅ | ✅ | — | ✅ |
| Verbatim excerpts pinned to byte-offset source spans | ✅ | — | — | — |
| Explainable per-result score decomposition | ✅ | — | — | — |
| Persistent local memory — re-query instantly, offline | ✅ | — | — | — |
| Query data stays on your machine | ✅ | — | — | — |
| API key / account | none | required | required | required |
| Cost per query | $0 | metered | metered | metered |
Feature standing as of July 2026 — check each vendor's docs for current state.
That last row compounds, because agents ask in bursts:
The same ten tools serve every kind of agent, over whichever surface fits: MCP for coding agents, REST for everything else, SDKs to embed, and framework wrappers to drop in.
wigolo serveOne process exposes a plain-JSON REST API next to the MCP transport. No MCP client needed, just curl:
wigolo serve # 127.0.0.1:3333 — loopback is open; off-loopback requires a token
curl -sX POST http://127.0.0.1:3333/v1/search \
-H 'Content-Type: application/json' \
-d '{"query":"local-first software","max_results":5}'
POST /v1/{tool} covers all ten tools, GET /openapi.json is the OpenAPI 3.1 contract, and /mcp + /sse serve remote MCP clients from the same port. Bind past loopback and a bearer token is required, so the server fails closed by default. Point n8n, a Hermes-style assistant, or any self-hosted agent at it. → REST API
Thin, typed clients with an embedded local mode that finds or starts the daemon for you. No separate serve step.
TypeScript — npm install wigolo-sdk (zero-dep; Node / Bun / Deno / edge):
import { createLocalClient } from 'wigolo-sdk/local';
const { client, close } = await createLocalClient(); // reuse a running daemon, or spawn one
const res = await client.search({ query: 'local-first web search', max_results: 5 });
console.log(res.results.map((r) => r.title));
await close(); // stops the daemon only if this call spawned it
Python — pip install wigolo (standard library only; sync + async):
from wigolo import local_client
with local_client() as client: # reuse a healthy daemon, or spawn one
res = client.search(query="local-first web search", max_results=5)
for r in res["results"]:
print(r["title"], r["url"])
Drop wigolo's tools into the framework you already use. You get the full ten-tool surface, including the cache / find_similar / research / agent that most framework web-tools don't ship:
| Framework | Package | What you get |
|---|---|---|
| LangChain | `wigolo-langchain |
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