OpenClaw does not come with one built-in search engine. It comes with a choice. The provider you pick determines whether your agent gets titles and snippets or full page content, whether it can reach JavaScript-heavy sites, and what you pay per query. That choice matters more than most setup guides suggest.

These are the best OpenClaw search providers available today, covering every combination of cost, capability, and privacy from fully managed APIs to zero-dependency local deployments.

OpenClaw's web_search tool accepts a query and returns results from whichever provider you have configured. At the configuration level, a provider is just a provider key under tools.web.search plus an API key. At the agent level, it is the difference between your agent finding pages and your agent actually reading them.

There are two types of integration on this list:

Native providers (Firecrawl, Brave, Perplexity) are configured directly in openclaw.json under tools.web.search.provider. They plug into the web_search tool that OpenClaw exposes to your agent automatically.

Skill/MCP-based providers (Tavily, SearXNG) install as separate capabilities alongside your existing setup. They give your agent additional search commands rather than replacing the native web_search tool.

Both types work. Which one you need depends on whether you want a drop-in replacement for the default search provider or an additional layer on top of it.

Firecrawl is the only OpenClaw search provider that can search, scrape, extract structured data, and run autonomous web research from a single integration.

Every other provider on this list does one thing: return search results. Firecrawl does four. OpenClaw supports it as the web_search provider, as dedicated plugin tools (firecrawl_search and firecrawl_scrape), as a fallback extractor for web_fetch, and as the firecrawl_agent for autonomous multi-step web research. The full integration is documented at docs.openclaw.ai/tools/firecrawl. When your agent needs to find information, extract specific fields from a page, convert a site to structured JSON, or autonomously gather data across multiple sources without being told exactly where to look, Firecrawl handles all of it.

The extraction engine supports multiple output formats: clean markdown, structured JSON with a custom schema, raw HTML, and onlyMainContent mode that strips navigation and boilerplate. That format flexibility means your agent can pull an entire article as markdown for summarization, extract a pricing table as JSON for comparison, or feed raw HTML to a downstream parser. The smart caching layer (configurable via maxAgeMs, defaulting to 2 days) means repeat fetches of the same page cost nothing.

• firecrawl_search: Web search with sources, categories, and optional scrapeResults to return full page content alongside results in one call
• firecrawl_scrape: Direct URL extraction with format control: markdown, JSON with schema, raw HTML, or main-content-only; proxy modes basic, stealth, and auto
• firecrawl_agent: Autonomous web extraction using natural language: give it a goal, it plans and executes multi-step research across the web without hand-holding
• web_fetch fallback: When Readability fails on a URL, Firecrawl kicks in automatically if an API key is configured
• extractMode + JSON schema: Extract only the specific fields you need from any page, returned as structured data your agent can act on directly
• maxAgeMs: Cache control for both scrape and fetch; defaults to 2 days, configurable per request

Configure:

{
  "plugins": {
    "entries": {
      "firecrawl": { "enabled": true }
    }
  },
  "tools": {
    "web": {
      "search": {
        "provider": "firecrawl",
        "firecrawl": {
          "apiKey": "FIRECRAWL_API_KEY_HERE",
          "baseUrl": "https://api.firecrawl.dev"
        }
      }
    }
  }
}

Or set FIRECRAWL_API_KEY as an environment variable and run openclaw configure --section web to choose Firecrawl as your provider. See the Firecrawl CLI docs for the full list of available commands.

Get a free API key at firecrawl.dev/app/api-keys.

Honest take: The gap between Firecrawl and every other provider on this list is the firecrawl_agent. Ask it "find the pricing plans for the top five CRM tools and return them as a comparison table" and it will plan the search, scrape the relevant pages, extract the data, and return structured output — without your agent manually coordinating each step. No other search provider in the OpenClaw ecosystem comes close to that level of autonomous capability. The scrapeResults option on firecrawl_search is also underrated: one call returns search results and scraped page content together, so your agent never has to do a separate fetch round-trip. For agents that do real research, not just keyword lookups, Firecrawl is the clear choice.

Cons: Credit-based pricing means heavy scraping adds up. The free tier (500 credits) covers experimentation but production research workflows will need a paid plan. The proxy: "auto" default uses more credits than basic-only mode. Switch to proxy: "basic" if your targets are reliably accessible and you are managing credit usage closely.

Full reference at docs.openclaw.ai/tools/firecrawl and Firecrawl's OpenClaw integration guide. For a deeper look at how web_search and web_fetch interact in practice, read OpenClaw Web Search: How to Make Your Agent Actually Read the Web.

Brave Search is the officially recommended OpenClaw search provider for general-purpose web queries.

The OpenClaw configuration wizard defaults to Brave if you run openclaw configure --section web with a Brave API key ready. Brave runs its own independent search index rather than proxying Google or Bing results, which makes it more privacy-friendly and less susceptible to SEO manipulation. Each Brave Search plan includes $5/month in free credit (renewing), covering roughly 1,000 queries per month at the Search plan rate of $5 per 1,000 requests. The Search plan also includes the LLM Context endpoint and AI inference rights.

• freshness: Filter results by recency with day, week, month, or year
• date_after / date_before: Pin results to a specific date range (YYYY-MM-DD format)
• country + language: Locale-specific results using ISO country and language codes
• cacheTtlMinutes: Results cached for 15 minutes by default, configurable
• Independent index: Does not depend on Google or Bing data

Configure:

{
  "tools": {
    "web": {
      "search": {
        "provider": "brave",
        "apiKey": "BRAVE_API_KEY_HERE",
        "maxResults": 5,
        "timeoutSeconds": 30
      }
    }
  }
}

Or set BRAVE_API_KEY as an environment variable.

Get an API key at brave.com/search/api/.

Honest take: Brave is the sensible default for most OpenClaw setups. The independent index produces clean results and the freshness and date filtering are genuinely useful for news-heavy or time-sensitive research tasks. The 1,000 queries per month on the free credit covers a typical personal agent. Where it falls short: results are titles and snippets only, no full page content. If your agent needs to actually read a page, pair Brave with Firecrawl as the web_fetch fallback.

Cons: Snippet-only results with no built-in content extraction. Rate limits on the free credit tier can become a constraint for agents that run multiple searches per conversation. Legacy Brave plans (the original free plan with 2,000 queries per month) remain valid but do not include the LLM Context endpoint or higher rate limits.

The latency issue is a real friction point that comes up in the community. Here is what one user shared on Reddit recently:

I'm running OpenClaw and finally got my Brave Search API integrated, but I'm hitting a wall. The web_search tool is noticeably slow — by the time it hits the API, gets the results, and the LLM processes them, I could have Googled it myself twice. I have access to the Brave Answers API, which is way faster for direct info, but OpenClaw doesn't seem to have a field for it. The config only has tools.web.search.apiKey for the standard Search API. Has anyone figured out a workaround to use the Answers API (or the new LLM Context endpoint) to speed this up? Or is there a way to tweak the search tool so it isn't such a bottleneck? Right now, having a 'pro' search key feels kind of useless if the integration is this sluggish.

Worth keeping in mind if your agent does frequent, latency-sensitive searches. Pairing Brave with Firecrawl as the web_fetch fallback helps on the content extraction side, but does not address the underlying API round-trip speed.

Full reference at docs.openclaw.ai/brave-search.

Tavily is an AI-optimized search API designed specifically for LLMs and agent research workflows.

Unlike Brave or Perplexity which return standard search result fields, Tavily is built from the ground up for agents: clean JSON responses, automatic answer extraction, and full article content instead of raw snippets. The tavily-search skill is one of the most widely used in the OpenClaw community for web research, fact-checking, and real-time information retrieval. Tavily's free tier includes 1,000 searches per month. Integration happens through a skill install rather than a native tools.web.search.provider setting, which means it layers on top of your existing setup rather than replacing it.

• Structured JSON responses with direct answer extraction surfaced at the top of results
• search_depth: basic (fast, suitable for most queries) or advanced (deeper sources, more comprehensive coverage)
• Include or exclude specific domains to restrict or block result sources
• Returns full article content, not just snippets
• Coexists with the native web_search provider: your agent uses Tavily for research-heavy queries and the built-in tool for direct URL fetches

Install:

/skill install @anthropic/tavily-search

Or configure manually in openclaw.json:

{
  "skills": {
    "tavily-search": {
      "apiKey": "tvly-your-api-key-here"
    }
  }
}

Get a free API key at tavily.com. The key starts with tvly-.

Honest take: Tavily produces noticeably better-structured output than raw web search results. The answer extraction means your agent does not have to infer the key point from a wall of text. For any agent doing multi-step research or fact-checking workflows, Tavily is worth the extra install step. The skill-based integration is slightly more setup than a native provider, but the quality difference on research queries is real.

Cons: Skill-based integration requires an explicit install step compared to native providers. The 1,000 searches per month free limit matches Brave. Advanced search mode is slower and counts against the same quota. When both Tavily and the built-in web_search provider are active, your agent may not always pick the right one for the task. Explicit prompting ("use Tavily to search for...") helps if you see inconsistent behavior.

Full reference at openclawlaunch.com/guides/openclaw-tavily. If Tavily does not fit your needs, see our Tavily alternatives roundup.

Perplexity gives OpenClaw two modes: structured web search results and AI-synthesized answers with citations.

Perplexity is a native web_search provider in OpenClaw (docs.openclaw.ai/perplexity) with a feature no other provider on this list offers: a dual-mode configuration. The native Perplexity Search API path returns structured results (title, url, snippet) like Brave. But point it at OpenRouter or set a baseUrl and model, and it switches to the Sonar chat-completions path and returns AI-synthesized answers with inline citations instead. The Search API path also has the richest filtering options of any native provider: domain_filter lets you allowlist or denylist up to 20 domains per query, and max_tokens can scale up to 1,000,000 for content-heavy extraction tasks.

• domain_filter: Allowlist (e.g., ["nature.com", ".edu"]) or denylist (prefix with -) up to 20 domains per query
• max_tokens: Total content budget per search (default 25,000, max 1,000,000)
• max_tokens_per_page: Per-page token limit (default 2,048, adjustable)
• freshness + date_after/date_before: Time filtering on the Search API path
• OpenRouter compatibility: Set baseUrl and model to switch to Sonar for AI-synthesized answers

Configure (native Perplexity Search API):

{
  "tools": {
    "web": {
      "search": {
        "provider": "perplexity",
        "perplexity": {
          "apiKey": "pplx-..."
        }
      }
    }
  }
}

Configure (OpenRouter/Sonar for AI-synthesized answers):

{
  "tools": {
    "web": {
      "search": {
        "provider": "perplexity",
        "perplexity": {
          "apiKey": "<openrouter-api-key>",
          "baseUrl": "https://openrouter.ai/api/v1",
          "model": "perplexity/sonar-pro"
        }
      }
    }
  }
}

Or set PERPLEXITY_API_KEY as an environment variable.

Get an API key at perplexity.ai/settings/api.

Honest take: The domain_filter parameter is the feature that makes Perplexity worth evaluating over Brave for technical or academic research. Restricting results to .gov, .edu, and nature.com meaningfully improves signal quality on topics where SEO noise is a problem. The Sonar mode is useful when you want synthesized summaries over raw results, though it is a different interaction pattern from every other provider.

Cons: The dual-mode setup is a source of confusion: switching from the Search API to Sonar changes the response format and disables most filter parameters (only query and freshness work on the Sonar path). If provider: "perplexity" is configured but the key is missing, OpenClaw fails fast at startup rather than silently degrading. No free tier is advertised in the OpenClaw documentation.

Full reference at docs.openclaw.ai/perplexity. For other search options with similar capabilities, see our Perplexity alternatives guide.

SearXNG is the zero-cost option: a self-hosted metasearch engine that requires no API key and has no query limits.

SearXNG is an open-source metasearch engine that queries multiple search backends simultaneously and aggregates the results. It runs entirely on your own machine or server, which means no API key, no monthly quota, and no third-party data logging. For privacy-conscious setups or situations where external search APIs are blocked or cost-prohibitive, it is the practical alternative. The OpenClaw integration is through a ClawHub skill by @adelpro that wraps SearXNG's local HTTP endpoint using curl and jq: run SearXNG in Docker, then the skill queries it directly on localhost:8080.

• No API key and no query limits: bounded only by your hardware
• Meta-search: aggregates results from Google, Bing, DuckDuckGo, and other configured backends simultaneously
• Privacy-first: users are not tracked or profiled; no query data leaves your infrastructure except to the search backends you enable
• Self-hosted: runs entirely on your machine or VPS
• Runtime requirements: docker, curl, jq

Setup:

# Step 1: Run SearXNG locally with Docker
docker run -d -p 8080:8080 searxng/searxng

Then install the OpenClaw skill from ClawHub:

Full skill reference and install at clawhub.ai/adelpro/private-web-search-searchxng.

Honest take: SearXNG is the right choice if you want unlimited searches with zero ongoing cost and have a machine or VPS to host it on. The privacy benefit is real: you control which search backends are active and nothing is logged by a third party. The setup is more involved than any other option here, but once running it is stable. Worth it for home server setups, privacy-sensitive deployments, or situations where you are running a high-volume agent and API costs are a concern.

Cons: Self-hosting carries maintenance overhead: container updates, firewall configuration to ensure the instance is only reachable on localhost, and the initial Docker setup. The ClawHub skill has a VirusTotal flag (marked suspicious), though OpenClaw's own security scan rates it benign with high confidence and the skill's behavior matches its stated purpose. Result quality depends on which SearXNG backends are active and can be inconsistent compared to dedicated AI-optimized APIs.

Full reference at clawhub.ai/adelpro/private-web-search-searchxng.

No single provider wins on every dimension. The combination that works depends on what your agent actually does.

For most setups, start with Brave as the native web_search provider and add Firecrawl as the web_fetch fallback via tools.web.fetch.firecrawl.apiKey. Brave handles the search, Firecrawl handles the pages that Brave's snippets do not fully cover. That two-provider stack costs roughly 1,000 Brave queries per month free and uses Firecrawl credits only when a page needs actual extraction.

For research-heavy agents (fact-checking, competitive monitoring, multi-step information gathering), Firecrawl is the right upgrade. Use firecrawl_agent to hand the entire research goal to Firecrawl and get back structured output, or use firecrawl_search with scrapeResults to get full page content alongside results in a single call. No other provider on this list handles that in one step. If your agent also needs to interact with pages rather than just read them, our browser automation tools comparison covers the options.

For technical or academic research where source quality matters, Perplexity's domain_filter is the tool that changes things. Being able to say "only return results from these 10 trusted domains" produces a fundamentally different result quality than keyword search on the open web.

For privacy-first or high-volume deployments where API costs become a concern, SearXNG removes the per-query cost entirely. It takes more setup but runs indefinitely on your own infrastructure.

The full OpenClaw documentation at docs.openclaw.ai is the authoritative reference for current provider configuration options. For a deeper look at how web_search and web_fetch interact, and how to configure Firecrawl for the full OpenClaw web stack, read OpenClaw Web Search: How to Make Your Agent Actually Read the Web. If you are building a Firecrawl-powered agent from scratch, the OpenClaw Firecrawl guide covers the full integration from API key to browser automation. For a broader look at evaluating web data tools for your agent stack, our guide on choosing web scraping tools covers how the options compare.