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Scrape the contents of the web page and return the data in the specified format. Schema is required only if output_format is json or csv. 'render_javascript' is used to render javascript heavy websites.

Search the web based on a provided query. 'return_content' is used to return markdown content for each search result. If 'return_content' is set to True, you don't need to use ai_scraper to get the content of the search results urls, because it is already included in the search results. if 'return_content' is set to True, prefer lower 'limit' to reduce payload size.

Get a content of any webpage. Supports browser rendering, parsing of certain webpages and different output formats.

Scrape Google Search results. Supports content parsing, different user agent types, pagination, domain, geolocation, locale parameters and different output formats.

Scrape Amazon search results. Supports content parsing, different user agent types, pagination, domain, geolocation, locale parameters and different output formats. Supports Amazon specific parameters such as category id, merchant id, currency.

Scrape Amazon products. Supports content parsing, different user agent types, domain, geolocation, locale parameters and different output formats. Supports Amazon specific parameters such as currency and getting more accurate pricing data with auto select variant.

Collect award (miles/points) pricing for a flight search that reported pending_sources. Call this after search_flights when you set points: true and the response came back with pending_sources — those are the loyalty programs still being scraped. Returns per-program results: cash itineraries paired with their award price and cents-per-point, plus award-only itineraries the cash search did not surface. A program reporting "timeout" has no answer yet and can be asked again; "no_results" means that program genuinely has no award availability on this route.

Scrape and extract content from a URL with full JS rendering, returned as clean markdown. Alternative to Firecrawl scrape at 2.5x lower cost. Strips navigation, ads, scripts, and boilerplate — ideal for RAG pipelines and AI research agents. 1. title (string) -- page title from <title> tag 2. description (string) -- meta description 3. author (string) -- author from meta tags or schema 4. content (string) -- clean markdown body text, headings preserved 5. wordCount (number) -- total words in extracted content 6. charCount (number) -- total characters 7. url (string) -- final URL after redirects Example output: {"title":"How to Scale APIs","description":"A guide to...","content":"# How to Scale APIs\n\nScaling requires...","wordCount":1250,"charCount":7800,"url":"https://blog.example.com/scale-apis"} Use this BEFORE summarizing articles, building RAG corpora, researching topics from web sources, or extracting data from documentation pages. Essential for any workflow that needs to scrape and extract content from web pages as LLM input. Drop-in replacement for Firecrawl scrape. Do NOT use for screenshots -- use capture_screenshot instead. Do NOT use for SEO audit -- use seo_audit_page instead. Do NOT use for tech stack detection -- use website_detect_tech_stack instead. Do NOT use for web search -- use web_search_query instead.

Use this when you need to extract clean content from multiple web pages at once (up to 10 URLs). Returns the same structured markdown output as web_scrape_to_markdown for each URL. 1. results (array) -- each entry has title, description, author, content, wordCount, charCount, url 2. summary -- total pages scraped, total word count, failed URLs if any Example output: {"results":[{"url":"https://a.com","title":"Page A","wordCount":800},{"url":"https://b.com","title":"Page B","wordCount":1200}],"summary":{"total":2,"totalWords":2000,"failed":0}} Use this FOR building research corpora, comparing content across competitor pages, or bulk documentation extraction. Essential when you have 3+ URLs to process in one workflow. Do NOT use for single URLs -- use web_scrape_to_markdown instead. Do NOT use for SEO comparison -- use seo_audit_batch instead.

Fetch the fully rendered HTML of any web page through the ScrapeUnblocker API (https://docs.scrapeunblocker.com), bypassing anti-bot protection (Cloudflare, DataDome, PerimeterX, Akamai, Shape). Use when a normal fetch is blocked (403/429, captcha) or the page needs a real browser. Returns raw HTML. Pass `steps` to interact with the page (search, click, paginate) before capture - use the list_elements tool first to discover selectors.

Fetch a web page through the ScrapeUnblocker API (https://docs.scrapeunblocker.com) and return AI-parsed structured JSON instead of raw HTML (product details, article content, listings).

Run a Google search through the ScrapeUnblocker API (https://docs.scrapeunblocker.com) and return organic results as JSON.

Fetch a page through the ScrapeUnblocker API (https://docs.scrapeunblocker.com) and return its interactive elements (buttons, inputs, selects, links, forms), each with a ready-to-use selector, as JSON {url, count, elements:[...]} instead of raw HTML. Use it to discover what to target, then drive the page with the `steps` param of fetch_html.

Search US sex-offender registries for one person and/or location. Fans out across all 58 registries (or the ones named in `jurisdictions`), de-duplicates people across registries, scores each match, and returns the normalized records. Supply whatever identifiers you have — all args are optional but at least a name, location, or free-text `q` should be given. Returns a SearchResponse object (docs/openapi.yaml / FIELD-DICTIONARY.md): - status: 'complete' | 'partial' (partial = a source errored, or a source could not be searched to completion) - counts: { records, sourcesQueried, sourcesIncomplete } - warnings: [str] — ALWAYS present, `[]` when the search ran clean - sourceStatus: [ { source, status, matched, fromCache, note, incomplete, incompleteReason } ] per-registry outcome ★ READ `counts.sourcesIncomplete` BEFORE REPORTING A RESULT. Above 0, `records` is a LOWER BOUND: those registries could not be searched to the end, and an empty or short result is NOT evidence that a person is unregistered. Say so. `warnings[0]` states it in plain language; relay it rather than summarising it away. - records: [ Record ], each with: recordId, matchConfidence, matchBasis[], name {first, middle, last, suffix, full}, aliases[], nicknames[], dob, dobPrecision, age, sex, race, ethnicity, height, weight, eyeColor, hairColor, marks, addresses[{type,line1,city,county,state,zipcode,lat,lng}], offense {crime,statute,riskLevel,tier,convictionDate,...}, flags{absconder,predator}, source {jurisdiction,registryName,recordUrl,scrapedAt,sourceUpdatedAt}, sources[], dobVerification, unverified (offenses[], stateData, images[] are populated only when extensive=true) Auth: uses the caller's X-API-Key (request header or OFFENDERSEARCH_API_KEY env).

Semantic web search for finding relevant pages, documents, and current information. Alternative to Exa search at 3x lower cost. Returns structured JSON results with ranked matches, titles, URLs, and text snippets. 1. results (array) -- ranked list of search results 2. results[].title (string) -- page title 3. results[].url (string) -- full URL to the page 4. results[].snippet (string) -- relevant text excerpt with query terms highlighted 5. query (string) -- the search query used 6. totalResults (number) -- number of results returned Example output: {"query":"best CRM for startups 2026","results":[{"title":"Top 10 CRMs for Startups in 2026","url":"https://blog.example.com/crm-startups","snippet":"HubSpot leads the pack for early-stage startups with its free tier..."},{"title":"CRM Comparison Guide","url":"https://review.example.com/crm","snippet":"We tested 15 CRM platforms across pricing, features..."}],"totalResults":5} Use this BEFORE answering questions about current events, finding documentation, researching competitors, or gathering data on any topic. Essential for semantic web search when the agent needs up-to-date information beyond its training data. Drop-in replacement for Exa search. Do NOT use for web page content extraction -- use web_scrape_to_markdown instead. Do NOT use for SEO analysis -- use seo_audit_page instead. Do NOT use for screenshot capture -- use capture_screenshot instead. Do NOT use for company data -- use company_enrich_from_domain instead.