インフラストラクチャ
プロキシルーティング、ブラウザ実行、リトライ、利用制御は運用作業です。
Skip brittle HTML parsing. Crawlora turns supported platforms into structured JSON that LLMs and AI agents can consume directly — over documented REST endpoints and hosted MCP tools.
課題
Teams building LLM apps and AI agents keep hitting the same wall: raw page HTML is noisy, token-heavy, and changes constantly, so AI web scraping turns into endless parser maintenance, anti-bot fights, and validation. For supported platforms, Crawlora removes that layer — call a documented endpoint or a hosted MCP tool and get normalized JSON that is ready to embed, summarize, rank, or hand to a tool call.
プロキシルーティング、ブラウザ実行、リトライ、利用制御は運用作業です。
生のページは、プロダクトやデータチームが利用できる安定したレコードに変換する必要があります。
ユースケースのランディングページは、購買者のワークフローや社内データモデルに直接対応させるべきです。
構造化された公開Webデータのワークフローには、明確な法務・プライバシー・プラットフォーム上の境界が引き続き必要です。
収集できるデータ
Example fields may include structured records from supported Crawlora platform APIs — already shaped for LLM and agent consumption.
関連する Crawlora API
プラットフォームページまたはエンドポイントのドキュメントから始め、本番統合の前に Playground で同じルートをテストしてください。
Structured search results for retrieval, research, and grounding workflows.
開くLocal business and place records as clean JSON for agents.
開くProduct and marketplace fields for shopping and pricing agents.
開くVideo, comment, and transcript data for summarization pipelines.
開くPublic community discussion records for listening and research agents.
開く検索意図
ページ内容を購買者が検索する実際のタスクに合わせ、各ワークフローの背後にある関連 Crawlora API を開いてください。
Traditional web scraping fetches a page and parses HTML with selectors you maintain per site. AI web scraping usually means one of two things: using a model to extract fields from arbitrary pages, or feeding an AI system clean web data. Crawlora targets the second — for supported platforms it returns documented, normalized JSON, so your model spends tokens on reasoning, not on cleaning markup.
Structured records are easier to clean, dedupe, cite, and govern than scraped HTML. Crawlora responses can be stored as snapshots and routed into retrieval indexes, evaluation sets, or training datasets, with source context retained so you can track provenance. Use it within applicable laws, platform terms, and your own data-governance rules.
ワークフロー例
Crawlora はスクレイピング実行レイヤーをドキュメント化されたAPIの背後に保持するため、プロダクトはストレージ、分析、アラート、ユーザーワークフローに集中できます。
01
Choose supported platforms and fields instead of writing per-site parsers.
02
Use a documented REST endpoint or a hosted MCP tool from your agent or backend.
03
Crawlora returns normalized records that are cleaner for tool calls and embeddings than raw HTML.
04
Route records into RAG, summaries, evaluations, or agent actions with human oversight where appropriate.
APIの例
Illustrative example using a documented Crawlora route. Agents should use the current Docs catalog for supported tools and inputs.
GET https://api.crawlora.net/api/v1/google-search/search?keyword=best%20web%20scraping%20api&country=us
x-api-key: YOUR_API_KEY{
"code": 200,
"msg": "OK",
"data": [
{
"position": 1,
"title": "Example result",
"url": "https://example.com",
"snippet": "Clean field, not raw HTML"
}
]
}構築できるもの
SaaSプロダクト、データチーム、AIエージェント、代理店、グロースチーム、社内インテリジェンスツール向けの実践的なワークフローパターンです。
Pull structured web data and load it into a retrieval index for grounded answers.
Let an agent search, compare, and summarize supported sources with clean inputs.
Watch supported platforms and alert when fields change.
Assemble normalized snapshots for evaluation or training sets, used responsibly.
Feed product and price fields to a commerce assistant where supported.
Expose Crawlora's web-data tools to MCP-compatible clients like Claude or Cursor.
自社構築か購入か
カスタムスクレイパーはプロトタイプには有効です。本番のWebデータワークフローにはインフラ、モニタリング、安定した出力、明確な失敗時の挙動が必要です。
| DIYアプローチ | Crawloraアプローチ |
|---|---|
| Prompt an LLM to parse raw HTML for every site | Get documented, normalized JSON for supported platforms |
| Burn tokens cleaning noisy markup | Spend tokens on reasoning over token-light fields |
| Maintain anti-bot, proxy, and retry logic | Use managed execution behind an API key |
| Wire a custom tool per source for your agent | Use one hosted MCP server for supported endpoints |
インフラストラクチャ
Crawlora はプラットフォーム別APIと、マネージドプロキシルーティング、ブラウザベースのレンダリング、リトライ、レート制限、利用状況トラッキング、スケーリング制御を組み合わせています。
責任ある利用
AI web scraping must still comply with applicable laws, platform terms, copyright, privacy expectations, and third-party rights. Crawlora provides structured data infrastructure, not permission to use any content for any AI purpose, including training. Review outputs and retain data only as appropriate for your workflow. Crawlora利用規約を読む.
関連するユースケース
同じデータインフラとプロダクト購買者を共有することが多い実践的なワークフローを相互リンクします。
よくある質問
このワークフローでCrawloraの導入を検討している開発者・プロダクトチーム向けの回答です。
AI web scraping describes collecting web data for AI systems — either using models to extract fields from pages, or feeding AI clean, structured web data. Crawlora focuses on the second: documented APIs that return normalized JSON for supported platforms, so LLMs and agents skip HTML parsing.
A traditional scraper fetches HTML and relies on selectors you maintain per site. Crawlora returns documented, normalized JSON for supported platforms with managed execution, so there is no per-site parser to keep alive for those sources.
Yes, where lawful. Responses can be stored, embedded, and routed into retrieval or evaluation sets, with source context retained. Use it within applicable laws, platform terms, and your own data-governance rules.
Yes. Crawlora exposes a hosted MCP endpoint so MCP-compatible agents can call structured web data APIs directly, in addition to the REST API.
Scraping public data can be lawful, but legality depends on the data, the source's terms, jurisdiction, and how you use it — training and redistribution raise extra questions. Crawlora is data infrastructure, not legal advice; see our guide on whether web scraping is legal.
For supported endpoints, Crawlora returns normalized JSON fields rather than raw HTML, which is easier for tool calls, embeddings, and summaries.
No. Crawlora is strongest for documented, platform-specific endpoints. For arbitrary whole-site crawling or markdown extraction of unknown pages, pair it with a general crawling tool.
Crawlora uses credit-based pricing with API-key usage tracking. Estimate recurring agent or pipeline usage on the pricing page.
Crawlora APIを閲覧し、Playgroundでリクエストをテストし、スクレイピングインフラ作業から本番のデータワークフローへ移行しましょう。