# Sparks RE API – Property Factual Extractor

> Sparks RE API – Property Factual Extractor is a paid API for AI agents from sparks-re-api.sparksdigital-re.workers.dev, paid per call via x402, $0.03/call, status unknown (last checked 2026-10-30).

Parses unstructured real estate listing text into structured property fields using regex pattern matching

## Facts

- Endpoint: POST https://sparks-re-api.sparksdigital-re.workers.dev/property/factual?utm_source=zero.xyz
- Price: $0.03/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-30
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/sparks-re-api-property-factual-extractor-d12d68bc
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_mNhlUesWysy01tpVvJ3IO

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 sparks-re-api-property-factual-extractor-d12d68bc -d '<json body>'
```

Example prompt: Can you pull the structured property details out of this MLS listing description — I need the address, bedrooms, bathrooms, square footage, lot size, year built, property type, and asking price as separate fields: '789 Maple Ave, Indianapolis IN 46220 — charming 3BD/2BA SFR built in 1998, 1,850 sqft on a 0.25-acre lot, listed at $295,000.'

## When to prefer this

Choose this endpoint when you have free-form or MLS listing text and need fast, cheap structured extraction of standard property fields without AI inference overhead. At $0.03/call it is cost-effective for high-volume pipelines. Prefer it over the AI-powered sibling endpoint when speed and cost matter more than handling edge cases, and over manual parsing when you need consistent JSON output. If the text is highly ambiguous or uses non-standard formats, consider the Gemini-powered sibling endpoint instead.

## Known failure modes

- Ambiguous or abbreviated text may cause fields to be null or incorrectly parsed — regex cannot handle all formatting variations
- Unconventional price formats (e.g. 'two ninety-five') may not be captured in raw_price
- property_type may default to null if not explicitly stated or not matching known abbreviations
- Heavily abbreviated MLS shorthand may fail to match regex patterns for square footage or lot size
- Non-US address formats may parse city/state/zip incorrectly or not at all
- Payment failure (insufficient USDC balance) returns 402 Payment Required

## How this service works

AI-powered real estate tools for property normalization, FHA compliance scanning, and investor metrics calculation. Powered by x402 micropayments.

## Output

A JSON object with up to 11 structured property fields: address, city, state, zip, bedrooms (integer), bathrooms (integer), square_feet (integer), lot_size (string), year_built (integer), property_type (string, e.g. 'SFR'), and raw_price (string). Fields not found in the input text may be null or omitted. Values are regex-parsed — agent should validate before downstream transactional use.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "raw_text": {
   "type": "string",
   "description": "Free-form property listing text to parse"
  }
 }
}
```

## Response schema (JSON Schema)

```json
{
 "type": "json",
 "example": {
  "zip": "46220",
  "city": "Indianapolis",
  "state": "IN",
  "address": "789 Maple Ave",
  "bedrooms": 3,
  "lot_size": "0.25 acres",
  "bathrooms": 2,
  "raw_price": "$295,000",
  "year_built": 1998,
  "square_feet": 1850,
  "property_type": "SFR"
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/sparks-re-api-property-factual-extractor-d12d68bc/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from sparks-re-api.sparksdigital-re.workers.dev](https://www.zero.xyz/host/sparks-re-api.sparksdigital-re.workers.dev/llms.txt)