RAW HTTP — NO HEADLESS BROWSER OVERHEADMARKDOWN · JSON · HTML · LLM-READY FORMATSMCP SERVER FOR AI AGENTSTLS FINGERPRINT IMPERSONATIONEXTRACT · SUMMARIZE · DIFF · BRANDSITEMAP DISCOVERY & DEEP CRAWLINGSELF-HOST OR USE OUR CLOUD APIBUILT IN RUST — FAST BY DEFAULTDEEP RESEARCH — AI SYNTHESIZES REPORTS FROM 50+ SOURCESWEB SEARCH — QUERY AND SCRAPE SEARCH RESULTS IN ONE CALLAGENT SCRAPE — GIVE A GOAL, AI EXTRACTS WHAT YOU NEEDURL MONITORING — WATCH PAGES FOR CHANGES WITH WEBHOOKSBONUS CREDITS — EARN FREE CREDITS BY STARRING AND REFERRINGRAW HTTP — NO HEADLESS BROWSER OVERHEADMARKDOWN · JSON · HTML · LLM-READY FORMATSMCP SERVER FOR AI AGENTSTLS FINGERPRINT IMPERSONATIONEXTRACT · SUMMARIZE · DIFF · BRANDSITEMAP DISCOVERY & DEEP CRAWLINGSELF-HOST OR USE OUR CLOUD APIBUILT IN RUST — FAST BY DEFAULTDEEP RESEARCH — AI SYNTHESIZES REPORTS FROM 50+ SOURCESWEB SEARCH — QUERY AND SCRAPE SEARCH RESULTS IN ONE CALLAGENT SCRAPE — GIVE A GOAL, AI EXTRACTS WHAT YOU NEEDURL MONITORING — WATCH PAGES FOR CHANGES WITH WEBHOOKSBONUS CREDITS — EARN FREE CREDITS BY STARRING AND REFERRING

POST /v1/research

AI-powered deep research across the web

Multi-source research with citations, fully automated.

webclaw's /v1/research endpoint takes a research question, finds relevant sources, reads them, cross-references facts, and returns a synthesized answer with citations. Perfect for building research agents, competitive intelligence tools, or automated knowledge base updates.

The problem

Manual research means copying URLs, pasting content into a document, and hoping nothing was missed. Simple search-and-summarize is shallow and misses context across sources. Building a real research agent requires chaining many APIs and handling edge cases.

The webclaw solution

One endpoint takes a question, plans research, executes multi-hop web searches, reads sources with automatic bot bypass, synthesizes findings, and returns structured output with citations. Async job model means long-running research does not block your application.

Why webclaw for deep research

  • Single endpoint replaces chaining search, scrape, and LLM APIs
  • Multi-hop reasoning across multiple sources
  • Structured output with citations and source URLs
  • Async job model for long-running research
  • Works on bot-protected sites that other tools cannot reach

Code example

TypeScript — deep research

import { Webclaw } from "@webclaw/sdk";

const wc = new Webclaw({ apiKey: "wc_..." });

// Start async research job
const job = await wc.research.create({
  query: "What are the latest developments in Rust async runtimes in 2026?",
  maxSources: 15,
  depth: "deep",
});

// Poll for results
const result = await wc.research.wait(job.id);

console.log(result.summary);      // Synthesized answer
console.log(result.sources);      // URLs with snippets
console.log(result.citations);    // Inline citation references

webclaw features for this use case

  • Multi-hop web search and scraping
  • Synthesized answers with citations
  • Async job model
  • Configurable depth and source count
  • Works on bot-protected sources

Frequently asked questions

How does webclaw research compare to a normal LLM with web search?

Standard LLM web search typically reads 1-3 top results and summarizes them. webclaw research performs multi-hop reasoning, follows links, reads 10-30 sources, cross-references facts, and handles bot-protected sites. Output includes full source URLs and citations.

Can I use webclaw research for competitive intelligence?

Yes. Point the research endpoint at questions like 'What features did competitor X ship in Q1 2026?' and it will search, read changelogs, blog posts, and release notes, then return a synthesized timeline with source citations.

How long does a research job take?

Shallow research (5 sources) typically completes in 20-60 seconds. Deep research (15-30 sources) can take 2-5 minutes. Both run as async jobs so your application does not block waiting.

Related reading

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