Data x402 offerings

JSON tools: flatten JSON to dot paths, or convert JSON rows to CSV online

Descriptive statistics summary (mean, median, variance, standard deviation, and 25th/75th/90th percentiles via linear interpolation, matching R and numpy's default "type=7" method) over a numeric array of up to 10,000 elements.

Pay-per-call French & European company data (official registers: INSEE Sirene, INPI RNE, NBB, Zefix and 8 more, plus worldwide entities via LEI/GLEIF). Every skill is a paid HTTP resource: send a JSON data part {"path": "/v1/..."} or {"skill": "<id>", "params": {...}}; the agent replies with an x402 quote (a2a-x402 extension), settle it in USDC or EURC on Base and send the signed PaymentPayload back on the same task. No account, no API key. Free text is not interpreted.

Structured data from an invoice: seller and buyer (name, address, tax ID), invoice number, dates, currency, line items, subtotal, tax, total and payment details, with null for anything absent. The arithmetic is checked (line sum against subtotal, subtotal plus tax against total) and mismatches are returned. PDF with a text layer by URL or base64, or plain text. Not live-checked: Workers AI is checked by the owner after the merge.

Structured data from a web page (url) or your own text: give a schema of up to 20 field names with what each holds, and get a JSON object with exactly those fields, null where the text does not state one. Llama 3.3 70B. Text is capped at 12,000 characters; a model answer that is not JSON is retried once, then not charged.

PDF to text: send an https link or base64 (up to 15 MB) and get the text page by page plus title, author, page count and dates. Text PDFs only: a scanned PDF without a text layer answers 422 and is not charged.

Repairs broken JSON: markdown fences, comments, trailing commas, single quotes, unquoted keys, Python literals (True, False, None) and truncated endings. Pure code first; the model is asked once only when code cannot repair it. Optional JSON Schema check covers type, required, properties, items, enum, minimum, maximum, minLength, maxLength and pattern. Input max 1 MB.

Keywords and keyphrases from a text by RAKE (Rose et al., 2010) in pure code: phrases between stopwords and punctuation, scored by word degree and frequency, with counts. Stopword lists for en, de, fr, es, it, pt, nl and tr. Body { text, language, limit }: up to 100 KB, limit 1 to 50.

Named entities in a text or a page: people, organisations, places, dates and money amounts (from the chat model), plus e-mail addresses, URLs and phone numbers (from patterns), each de-duplicated with a count. With url, the page's readable text is used (robots.txt is respected).

Turn any PDF or image URL into structured data - metadata, extracted text, sliced page ranges, OCR for scanned docs, decoded barcodes / QR codes - without falling back to a vision LLM guess. Built for the messy 30% of documents where pdf-to-markdown alone returns nothing useful. Document intelligence skill pack: one x402 payment runs 7 underlying tools (pdf-info, pdf-to-markdown, pdf-extract-pages, image-ocr, barcode-decode, pdf-merge, images-to-pdf); partial-success per step.

Validate, pretty-print, and convert JSON to CSV in one pass - the complete JSON processing workflow. JSON pipeline skill pack: one x402 payment runs 3 underlying tools (json-validate, json-format, json-to-csv); partial-success per step.

Statistical analysis suite: descriptive statistics, correlation analysis, and outlier detection on a single dataset. Number crunch skill pack: one x402 payment runs 3 underlying tools (stats-summary, correlation, outliers); partial-success per step.

Full PDF processing pipeline - metadata, markdown conversion, and first-page extraction in one call. PDF processing pipeline skill pack: one x402 payment runs 3 underlying tools (pdf-info, pdf-to-markdown, pdf-extract-pages); partial-success per step.

Turn a wall of dirty text - chat logs, scraped pages, user-generated content, log dumps - into something safe to store, search, and pipe into the next step. Measure first, redact PII before anything else touches the data, then dedupe, sort, extract entities, surface keywords, and grade the readability of what's left. Text hygiene skill pack: one x402 payment runs 7 underlying tools (text-stats, redact, dedupe-lines, sort-lines, extract-entities, keywords, readability); partial-success per step.

Extracts solar incentives and rebates from text or documents.

Compare source coverage on exactly the same declared record cohort across two snapshots. Report per-record gained/lost sources, per-source count changes, and global coverage drift. Reject unknown sources or missing/duplicate records. Coverage does not establish source quality.

Space Markets Index (SMI), published by Space Markets, Inc.: orbital launch activity from public data. Weekly 2026 launch series, per-launch records (rocket, mission, payloads, mass status) and SMI prints, as small JSON. Each read costs $0.01 test USDC via x402 on Base Sepolia (testnet). Data: GCAT (J. McDowell, planet4589.org), CC BY 4.0, modified by Space Markets. Not affiliated with or endorsed by SpaceX. Data only, not advice. Free: https://smx.space/smi-api/latest

Treats cells at or above a caller threshold as foreground, labels four-neighbor connected components, and reports area, bounding box, peak, and mean value. It does not ingest imagery, calibrate backscatter, remove speckle, geolocate pixels, classify objects, or infer real-world meaning.

Audits SPC data for energy bill toolkit workflows.

Cross-Chain Supply Reconciliation analyses only the evidence supplied by the caller. It does not claim to query a chain, identify a legal status or replace an independent audit. Missing signals lower confidence and are listed explicitly; every classification includes the exact thresholds used.

Fetch items from an Apify Actor run default dataset. Body: { "token": "..." } from actors/call. First call per wallet pays via x402 proportional to Apify usage (capped at $1.00); SIWX replay is free.…

Convert flat tabular JSON (array of objects, or {meta, data, result_type}) to TOON, a compact pipe-delimited text format with ~60-70% fewer tokens than JSON. $0.005 per call via x402 USDC on Base or Solana, or a bearer token.

Convert flat tabular JSON (array of objects, or {meta, data, result_type}) to TOON, a compact pipe-delimited text format with ~60-70% fewer tokens than JSON. $0.005 per call via x402 USDC on Base or …

Descriptive statistics for an array of numbers: count, sum, mean, median, mode, min, max, range, variance, stddev, and percentiles.