# manylives.me Structured Field Extractor

> 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.

## Facts

- Endpoint: POST https://manylives.me/paid/text/extract?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-09
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/manylives-me-structured-field-extractor-1a0f51c0
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_I32yw10pUwJbXBMl7YuC2

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability manylives-me-structured-field-extractor-1a0f51c0 -d '<json body>'
```

Example prompt: Pull out the invoice_number, vendor, total, and due_date from this text and give me the results as structured fields: 'Invoice 1042 from Acme Pty Ltd. Total due AUD 120.00 by 1 November 2026.'

## When to prefer this

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.

## Known failure modes

- 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

## 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.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "text": {
   "type": "string",
   "examples": [
    "Invoice 1042 from Acme Pty Ltd. Total due AUD 120.00 by 1 November 2026."
   ],
   "description": "the text (required, max 20,000 chars)"
  },
  "fields": {
   "type": "string",
   "examples": [
    "invoice_number,vendor,total,due_date"
   ],
   "description": "comma-separated field names (required), e.g. total,due_date,vendor"
  }
 }
}
```

## Response schema (JSON Schema)

```json
{
 "type": "json",
 "example": {
  "fields": [
   {
    "name": "total",
    "value": "AUD 120.00"
   },
   {
    "name": "due_date",
    "value": "2026-11-01"
   }
  ]
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/manylives-me-structured-field-extractor-1a0f51c0/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from manylives.me](https://www.zero.xyz/host/manylives.me/llms.txt)