OpenClaw Search After Brave Paywall and DDG Antibot

OpenClaw users are losing their free search options. Brave Search API now gives just $5 in free credit per month before requiring payment at $5/1K requests. DuckDuckGo's Instant Answer API returns pre-computed answers, not actual search results -- useless for agents that need real web data. And direct scraping of search engines hits antibot walls within minutes. Here is what actually still works.

What happened to Brave's free tier

Brave Search API used to be the default recommendation for budget-conscious agent builders. The $5 free credit/mo now covers roughly 1,000 requests -- enough for testing, not for production. Beyond that, pricing is $5/1K requests ($0.005/request). The API itself works well: structured results, good coverage, reasonable latency. The problem is purely economic for teams that were relying on free access.

DuckDuckGo: the wrong kind of API

DuckDuckGo's Instant Answer API is not a search API. It returns pre-computed answers from sources like Wikipedia -- essentially an encyclopedia lookup. If you search for "best CRM for startups 2026" you get nothing useful. There is no way to get actual web search results from DuckDuckGo programmatically. The API that most tutorials reference does not do what agent builders need.

Self-hosted SearXNG: fragile in practice

SearXNG is the open-source metasearch engine that queries multiple search engines and aggregates results. In theory, it is free and self-hosted. In practice, upstream search engines block SearXNG instances aggressively. Google blocks within hours. Bing is slightly more tolerant but still rate-limits. You end up maintaining a rotating proxy setup that costs more in infrastructure and debugging time than just paying for a search API.

Direct scraping: an arms race you will lose

Scraping Google directly with Selenium or Playwright triggers CAPTCHAs within 50-100 requests from a single IP. Proxy rotation helps, but residential proxies cost $5-15/GB. Google actively fingerprints headless browsers. The cost and maintenance overhead of keeping a scraper alive exceeds the cost of a commercial search API for any volume beyond trivial.

What works for OpenClaw and similar agent frameworks

The realistic options in 2026: pay for a search API (Brave at $5/1K, SerpAPI at $25-$150/mo for 5K-15K searches, or Scavio at $30/mo for 7K credits), or accept limited search capability. There is no reliable free option at production volumes. The cheapest path is a pay-per-use API where you control exactly how many searches the agent makes.

import requests, os

API = "https://api.scavio.dev/api/v1/search"
H = {"x-api-key": os.environ["SCAVIO_API_KEY"]}

def agent_search(query: str, num_results: int = 5) -> list[dict]:
    """Search function for OpenClaw or any agent framework."""
    resp = requests.post(API, headers=H, json={
        "query": query,
        "platform": "google",
        "num_results": num_results
    })
    resp.raise_for_status()
    results = resp.json().get("organic_results", [])
    return [
        {
            "title": r.get("title", ""),
            "url": r.get("link", ""),
            "snippet": r.get("snippet", ""),
        }
        for r in results
    ]

# Integration with an agent tool definition
SEARCH_TOOL = {
    "name": "web_search",
    "description": "Search the web for current information",
    "parameters": {
        "type": "object",
        "properties": {
            "query": {"type": "string", "description": "Search query"}
        },
        "required": ["query"]
    }
}

def handle_search_tool(arguments: dict) -> str:
    """Handler for the web_search tool call."""
    results = agent_search(arguments["query"])
    # Format for LLM consumption
    formatted = []
    for i, r in enumerate(results, 1):
        formatted.append(f"{i}. {r['title']}\n   {r['url']}\n   {r['snippet']}")
    return "\n\n".join(formatted)

Cost control for agent search

The biggest risk with agent search is runaway costs. An agent that decides to search 50 times per task will burn through credits fast. Implement a per-task search budget: set a maximum number of searches per agent invocation and track usage. Most agent tasks need 3-5 searches, not 50.

class SearchBudget:
    """Enforce per-task search limits for agent frameworks."""

    def __init__(self, max_searches: int = 5):
        self.max_searches = max_searches
        self.used = 0

    def search(self, query: str) -> list[dict] | str:
        if self.used >= self.max_searches:
            return f"Search budget exhausted ({self.max_searches} searches used)"
        self.used += 1
        return agent_search(query)

    @property
    def remaining(self) -> int:
        return self.max_searches - self.used

# Per-task budget: 5 searches max
budget = SearchBudget(max_searches=5)
results = budget.search("OpenClaw agent framework docs")
print(f"Searches remaining: {budget.remaining}")

How Scavio fits

Scavio works as a drop-in search backend for OpenClaw and similar agent frameworks. The free tier at 250 credits/mo covers light development and testing. At $0.005/credit ($30/mo for 7K), it is price-competitive with Brave ($5/1K = $0.005/request) and cheaper than SerpAPI at higher volumes. The API returns structured JSON with organic results, AI overviews, and related questions -- all the data an agent needs to ground its responses.