Infrastructure
Proxy routing, browser execution, retries, and usage controls are operational work.
Give your agents a live web-search tool. Crawlora returns Google, Bing, and Brave search results and news as structured JSON over documented REST endpoints and hosted MCP tools — so models can search the web at run time.
The problem
Models cannot answer about anything after their training cutoff, and most search APIs are built for browsers, not agents: results arrive as HTML or sit behind quotas and per-engine SDKs. Agent builders end up wiring a different tool per engine and parsing markup. Crawlora gives agents one documented web-search tool — Google, Bing, and Brave results plus news as normalized JSON — callable over REST or hosted MCP tools.
Proxy routing, browser execution, retries, and usage controls are operational work.
Raw pages must become stable records before products and data teams can use them.
Use-case landing pages should map directly to buyer workflows and internal data models.
Structured public web data workflows still need clear legal, privacy, and platform boundaries.
What you can collect
Example fields may include search result positions, titles, URLs, snippets, and news metadata across supported engines.
Relevant Crawlora APIs
Start from the platform page or endpoint docs, then test the same route in Playground before production integration.
Structured Google search results for retrieval and grounding.
OpenBing web search results as normalized JSON.
OpenIndependent-index Brave search results for diversity.
OpenQuery Google web results with country and language inputs.
OpenFetch news headlines and sources for fresh, time-sensitive context.
OpenSearch intent
Match the page content to the practical jobs buyers search for, then open the relevant Crawlora APIs behind each workflow.
Register Crawlora's search endpoints as a tool your model can call when it needs current information. The agent issues a query, Crawlora returns ranked results as JSON, and your model reasons over titles, snippets, and URLs — then optionally fetches deeper data from Crawlora's other documented endpoints. It is callable from any framework over REST, or natively over hosted MCP tools.
Crawlora returns structured search results and news — positions, titles, URLs, snippets, and metadata — not cleaned page content or a generated answer. If your pipeline needs full article text, pair search with Crawlora's documented platform endpoints (for example YouTube transcripts or Reddit threads) or your own fetch-and-clean step. This keeps the search layer fast, predictable, and token-light.
Example workflow
Crawlora keeps the scraping execution layer behind documented APIs so your product can focus on storage, analysis, alerts, and user workflows.
01
Add the Crawlora search endpoint or MCP tool to your agent's toolset.
02
The agent calls search with a query, country, and language when it needs live information.
03
Your model reads ranked titles, snippets, and URLs instead of parsing HTML.
04
Follow up with documented platform endpoints for transcripts, threads, or product data.
05
Keep result URLs so the agent's answer can cite its sources.
API example
Illustrative example using the documented Google search route. Agents should use the current Docs catalog for supported inputs and fields.
GET https://api.crawlora.net/api/v1/google-search/search?keyword=latest%20web%20scraping%20regulations&country=us
x-api-key: YOUR_API_KEY{
"code": 200,
"msg": "OK",
"data": [
{
"position": 1,
"title": "Example result",
"url": "https://example.com",
"snippet": "Clean, ranked field for the agent to reason over"
}
]
}What you can build
These are practical workflow patterns for SaaS products, data teams, AI agents, agencies, growth teams, and internal intelligence tools.
Let an agent search the live web, compare sources, and summarize with citations.
Add live search to a RAG app so answers include current information.
Query Google, Bing, and Brave behind one endpoint for result diversity.
Surface fresh headlines and sources for time-sensitive questions.
Expose web search to MCP-compatible clients like Claude or Cursor.
Trigger searches from n8n, Make, or Zapier and route results downstream.
Build or buy
Custom scrapers can work for prototypes. Production web data workflows need infrastructure, monitoring, stable output, and clear failure behavior.
| DIY approach | Crawlora approach |
|---|---|
| Wire a separate SDK and parser per search engine | Call one documented endpoint across Google, Bing, and Brave |
| Handle quotas, keys, and HTML parsing yourself | Receive normalized JSON behind one API key |
| Build a custom agent tool per source | Use hosted MCP tools for supported endpoints |
| Spend tokens cleaning markup | Reason over token-light ranked results |
Infrastructure
Crawlora combines platform-specific APIs with managed proxy routing, browser-backed rendering, retries, rate limits, usage tracking, and scaling controls.
Responsible use
Use web search results responsibly and within applicable laws, search-engine terms, and third-party rights. Crawlora returns structured public search results, not cleaned page content or an authoritative answer, and results may be delayed, incomplete, or affected by upstream changes. Read Crawlora terms.
Related use cases
Cross-link practical workflows that often share the same data infrastructure and product buyers.
FAQ
Answers for developers and product teams evaluating Crawlora for this workflow.
It is an API that lets an LLM or agent search the live web as a tool and get results as structured JSON. Crawlora returns Google, Bing, and Brave results plus news that a model can reason over, over REST or hosted MCP tools.
This page is about live web search as an agent tool — issuing a query and getting ranked results at run time. Web Data for RAG is about collecting and embedding sources into a retrieval index. They compose well: search for freshness, RAG for grounding.
No. Crawlora returns structured search results and news metadata, not cleaned page content or a generated answer. Pair search with documented platform endpoints or your own fetch step when you need full text.
Google, Bing, and Brave search endpoints are documented, plus news endpoints. Using more than one engine improves result diversity and resilience.
Yes. Crawlora exposes a hosted MCP endpoint so MCP-compatible clients such as Claude or Cursor can use web search as a tool, in addition to the REST API.
Yes. The REST endpoints work with any HTTP client, and there are integration guides for LangChain, LlamaIndex, OpenAI Agents, n8n, Make, and Zapier.
Search and news endpoints return current public results at request time, subject to upstream availability. Coverage and freshness can vary by query and engine.
Crawlora uses credit-based pricing with API-key usage tracking. Estimate recurring agent search usage on the pricing page.
Browse Crawlora APIs, test a request in Playground, and move from scraping infrastructure work to production data workflows.