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manylives.me Structured Field Extractor
x402
manylives.me Structured Field Extractor is a paid API for AI agents from manylives.me, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-09).
Extracts user-specified fields from free-form text and returns them as structured JSON, with null for any fields not found.
Price / call$0.01
Success—
StatusUnknown
How this service works
Pull structured fields out of free text: name the fields you want and get JSON back (missing fields come back null). For invoices, emails, listings, bios and more.
Output
A JSON array of field objects, each containing a 'name' (the field you requested) and a 'value' (the extracted text from the input), or null if the field could not be found in the provided text.
Example use cases
Invoice data extraction for accounting
“Extract the invoice_number, vendor, total, and due_date from this invoice text: 'Invoice #8821 issued by TechSupply Co. Amount owed: $4,350.00 USD, payment due by December 15 2025.'”
Job listing parser for recruitment tool
“From this job posting, pull out the job_title, company, location, and salary fields: 'Senior Data Engineer at StreamFlow Inc., based in Austin TX. Salary range $140k–$170k per year. Apply by Jan 31.'”
Contact bio structured data extraction
“I have this short bio — can you extract the person_name, job_title, company, and email from it? 'Jane Hartwell is a Principal Architect at BlueSky Systems. She can be reached at j.hartwell@bluesky.io.'”
Technical details
Endpoint
POSThttps://manylives.me/paid/text/extract?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to pull specific, named fields from arbitrary free-form text and want structured JSON back in a single call. It is ideal for documents like invoices, emails, bios, and listings where field names are known in advance but text layout is inconsistent. Prefer it over regex or rule-based parsers when text format varies widely, and over general LLM calls when you want a clean, schema-consistent JSON result with explicit null handling for missing fields.
Side effects
- Text exceeds 20,000 character limit — request rejected
- Fields parameter missing or empty — extraction cannot proceed
- Requested fields not present in text — returned as null values
- Ambiguous or malformed text yields inaccurate or null extractions
- Very short or context-free text may cause incorrect field mapping
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| text | string | the text (required, max 20,000 chars) |
| fields | string | comma-separated field names (required), e.g. total,due_date,vendor |
Output
Schema · Response
{
"type": "json",
"example": {
"fields": [
{
"name": "total",
"value": "AUD 120.00"
},
{
"name": "due_date",
"value": "2026-11-01"
}
]
}
}Tags
x402
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