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Structured Web Data for AI Agents

Give AI agents cleaner, more reliable inputs than raw HTML by connecting them to Crawlora's platform-specific public web data APIs.

Agent tool layerNormalized JSONBounded toolsCost controls
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Verified HTTP pattern

POST /google/search

Normalized JSON

Request

POST https://api.crawlora.net/api/v1/google/search
x-api-key: $CRAWLORA_API_KEY
Content-Type: application/json

{
  "country": "us",
  "keyword": "best CRM software",
  "language": "en",
  "limit": 10,
  "page": 1
}

Base URL

https://api.crawlora.net/api/v1

Auth header

x-api-key

Example endpoint

POST /google/search

Crawlora helps agents work with predictable structured data from supported public platforms instead of brittle raw page inputs.

Developer workflow

Why raw browsing is not enough

Raw pages can be noisy, dynamic, incomplete, or hard to parse. Agents work better when tools return structured JSON with predictable fields.

Developer workflow

Crawlora agent tool categories

Search research

Google Search, Bing, and Brave endpoints where supported.

Open guide

Local business research

Google Maps local business data.

Open guide

Creator intelligence

TikTok and YouTube creator and video workflows.

Open guide

Video understanding

YouTube transcripts, captions, and metadata where supported.

Open guide

App intelligence

App Store and Google Play metadata and reviews.

Open guide

E-commerce intelligence

Amazon product and marketplace data.

Open guide

Startup research

Product Hunt product and launch endpoints.

Open guide

Reviews and business intelligence

Trustpilot, SimilarWeb, and LinkedIn endpoints where supported.

Open guide

Developer workflow

Agent architecture

01

Planner decides

The agent identifies which public data source is needed.

02

Tool layer calls Crawlora

A narrow server-side tool calls one Crawlora endpoint.

03

Crawlora returns JSON

The API returns normalized data and status information.

04

Agent uses output

The agent summarizes, ranks, compares, or stores the results.

Developer workflow

Example tool schema

Illustrative schema for a Google Search agent tool.

Tool schema · json

{
  "name": "crawlora_google_search",
  "description": "Search public Google results through Crawlora and return structured JSON.",
  "parameters": {
    "type": "object",
    "properties": {
      "query": { "type": "string" },
      "country": { "type": "string", "default": "us" },
      "language": { "type": "string", "default": "en" },
      "limit": { "type": "number", "default": 10 }
    },
    "required": ["query"]
  }
}

Developer workflow

Example outputs agents can consume

  • Ranked search results.
  • Local business candidates.
  • Review summaries.
  • Creator and video metadata.
  • Transcripts.
  • Product fields.
  • Startup launch records.

Developer workflow

Cost and safety controls

  • Bound result counts.
  • Add user-level quotas.
  • Cache repeated requests.
  • Log usage.
  • Expose only approved tools.
  • Avoid sensitive personal data collection.
  • Review terms.

Responsible public web data workflows

Use Crawlora for structured public web data workflows. Customers are responsible for compliance with applicable laws, third-party rights, platform rules, and Crawlora terms. Keep API keys server-side, validate inputs, and avoid collecting or storing unnecessary sensitive data.

Read Crawlora terms

Developer workflow

Related developer links

Use these pages to move between endpoint discovery, examples, pricing, and responsible-use guidance.

MCP

OpenAI Agents

LangChain

TypeScript guide

Python guide

Developer workflow

FAQ

Common questions for this Crawlora developer integration path.

Why use Crawlora instead of letting agents browse websites directly?

Structured JSON is easier for agents to validate, summarize, and store than raw HTML from arbitrary pages.

What data sources can agents access through Crawlora?

Supported sources include search, maps, TikTok, YouTube, Amazon, App Store, Google Play, Product Hunt, Trustpilot, SimilarWeb, LinkedIn, and more where available in the docs catalog.

Can Crawlora return JSON for LLM workflows?

Yes. Crawlora endpoints return normalized JSON for supported public web data workflows.

Can I use Crawlora with MCP?

Yes. Use Crawlora's MCP-ready metadata where supported or wrap HTTP endpoints in your own MCP server.

Can I use Crawlora with LangChain?

Yes. Create custom tools or document loaders around Crawlora HTTP calls.

Can I use Crawlora with OpenAI Agents?

Yes. Expose Crawlora endpoints as callable tools with narrow schemas and server-side API keys.

How do I keep agent usage safe and cost-controlled?

Use bounded result counts, approved tool lists, quotas, caching, usage logs, and responsible-use review.

Next step

Design your first agent tool

Choose one Crawlora endpoint, define a narrow schema, and give the agent structured output with clear failure states.

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