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Money AI – Extract Named Fields from Text
x402
Money AI – Extract Named Fields from Text is a paid API for AI agents from money-ai-shop.money-ai.workers.dev, paid per call via x402, $0.006001/call, status unknown (last checked 2026-09-14).
Pulls specified named fields (e.g. name, email, amount, date) out of a short text blob and returns them as structured JSON.
Price / call$0.006001
Success—
StatusUnknown
How this service works
Pull named fields out of a short blob of text as JSON. Use it for: Extract name, email and company from this signature block.; Extract amount, currency and due date from this invoice line.
Output
A JSON object containing the named fields requested in the brief, with values pulled directly from the supplied text. Each field name corresponds to a key, and the extracted value is the corresponding value. Missing fields may be null or absent.
Example use cases
Extract contact info from email signature
“From this signature block, extract the person's name, email, company, and phone number as structured JSON: 'Sarah Lee | Director of Sales | Brightline Inc | sarah.lee@brightline.com | 020 7946 0123'.”
Parse invoice line item details
“I've got an invoice line that reads: 'Invoice #4421 – Amount due: £2,350.00 GBP – Due date: 15 August 2025 – From: Vertex Consulting Ltd.' Can you extract the invoice number, amount, currency, due date, and supplier name from it?”
Structured data from job posting snippet
“Pull out the job title, company name, location, and salary range from this job posting snippet: 'Senior Product Manager at NovaTech – London, UK – £80,000–£95,000 per annum – Apply by 30 June 2025.'”
Technical details
Endpoint
POSThttps://money-ai-shop.money-ai.workers.dev/s/extract-fieldsWhen to prefer
Choose this endpoint when you have a short, unstructured text blob and need to pull out specific named fields into a structured JSON object quickly and cheaply. It is ideal for signature blocks, invoice lines, payment notes, job snippets, and similar short-form business text. Prefer it over general LLM calls when you want a purpose-built, low-latency, pay-per-use extraction with no setup overhead.
Side effects
- Text too long or complex — service is optimized for short blobs, may truncate or miss fields
- Ambiguous field names in the brief — may extract wrong values if the instruction is unclear
- Field not present in text — may return null, empty string, or omit key
- Malformed brief — if the instruction doesn't specify fields clearly, output quality degrades
- Rate limit or payment failure — x402 payment rejected or insufficient USDC balance
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| brief | string | what you want produced |
| skill | string | which service to run |
Tags
x402
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