56 services carry this tag in their source record. Tags come from the provider, not from us — a tag is a claim about what the service does, not proof that it does it well.
Verified reference record for one niche fashion subculture: years, key brands, iconic items, music, where to buy, a price range, and a WARNING note on what it must not be confused with. Call it before recommending brands...
Argentina official gazette (Boletin Oficial) keyword search returning literal excerpts of matching notices with dates and source URLs; an optional date limits the search to that day's notices. Use this when an agent need...
Fetch any URL (web scraping / URL fetch) and get the raw content: HTML/JSON/text as text, images and PDFs as base64 (for multimodal LLM input), or markdown. Final URL after redirects, status, content type, size. Fetched...
Compress long documents and RAG inputs into token-budgeted, deduplicated context packs with source-linked provenance. Returns original and compiled token counts, so the saving is verifiable. Net-positive above N = fee /...
Fetch one public static HTML page after robots and public-address checks, then return bounded readable text, title, final URL and source links. Standard x402: POST the URL, sign the 402 and resend the same body. The 402...
PDF to text: give a PDF URL, get the text of every page with the title, author and page count. For RAG, research and summarizing reports, filings and papers.
Fact-check one claim against live web sources (or URLs you supply). Returns a verdict (supported, refuted, mixed, insufficient), a confidence score and supporting or contradicting quotes that are checked verbatim against...
Cited answer (RAG): a natural-language question is answered by searching the public web, reading the top pages and synthesizing a grounded answer with a list of source URLs. Answer cites only the retrieved sources (anti-...
Web search results. Search the web and get the top results as JSON: title, URL, a short snippet and the page age, from the Brave Search API. 1-20 results per call. Results are for the caller's immediate use only: no stor...
Given the URL of a public PDF, returns its text as markdown with tables as markdown tables, page by page (up to 30 pages per call, choose pages with e.g. 1-10), plus page count, title, word and table counts and pages tha...
Generate a text embedding vector using OpenAI text-embedding-3-small (1536 dimensions). Ideal for semantic search, RAG, and clustering. No API key needed; pay per call via x402. Text capped at 32k chars.
Webpage text extraction: extract clean text from any webpage. Extract the clean readable text from a public webpage with title, headings, links and SHA-256; add format=markdown for Markdown or render=true to render JavaS...
Drop-in Tavily-compatible search: the same request (query, search_depth basic / advanced, topic general / news, max_results, include_answer, include_raw_content, include_domains, exclude_domains, time_range, days) and re...
Read multiple web pages for AI agents: give up to 5 URLs, get the full clean text of each page, rendered in a real browser so JavaScript sites work, with title and final URL, in one call and one payment. For RAG, researc...
Web-content reader: fetch any http(s) URL and return clean readable text, title/description/canonical, and outbound links as JSON — the data an agent ingests on each step of a crawl or RAG loop. Input: url.
Split long text into overlapping chunks for RAG and embeddings, by characters, words or estimated tokens, keeping sentences or paragraphs whole, with each chunk's position and size.
Classify sentiment (positive/negative) with DistilBERT. POST text; returns label and confidence score. Fixed low per-request price.
Drop-in Exa-compatible search: the same request (query, numResults, category, includeDomains, excludeDomains, startPublishedDate, contents.text, contents.highlights) and response format (results with id, title, url, publ...
OpenAI-compatible text embeddings over x402 (768-dim, up to 32 inputs per call) — Genesis402 / UnyKorn Operator Network
Generate sentence embeddings (all-MiniLM-L6-v2, 384-dim, mean-pooled + L2-normalized) for up to 96 texts per call. Drop-in compatible with any all-MiniLM-L6-v2 index. Pairs with /chunk for a complete RAG pipeline.
Real-time news search for AI agents. Returns recent news articles (title, link, snippet, published date) as JSON from a multi-engine news metasearch. Pay-per-query in USDC via x402 — no signup, no API key. Use for curren...
Text embeddings for semantic search and RAG: one vector per call, 1024 dimensions.
Web research. One call to research a question on the web: a Brave web search, then the text of the top 1-5 result pages, read in parallel and clipped to your length, with titles and URLs. A page that cannot be read is li...
Read any public web page and get its main content as clean Markdown (menus, ads and footers removed) with title, author, publish date and language. Use when you need to read, quote or summarise an article, docs page or b...