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24K Labs Entity Extractor
x402
24K Labs Entity Extractor is a paid API for AI agents from api.24klabs.ai, paid per call via x402, $0.002/call, status unknown (last checked 2026-09-13).
Extracts structured entities (URLs, emails, and mentions) from freeform text, returning categorized lists in a single call.
Price / call$0.002
Success—
StatusUnknown
How this service works
A curated directory of x402 services — each one on the list on purpose, with the health, uptime, and independent trust grades from across the ecosystem gathered in one place.
Output
Returns a JSON object with a total entity count and a nested entities object containing three arrays: urls (all HTTP/HTTPS links found), emails (all RFC-5322-style email addresses found), and mentions (all @handle references found) in the input text.
Example use cases
Contact harvesting from support emails
“I have a bunch of raw customer support emails — can you pull out all the email addresses and URLs mentioned in this message body: 'Hi, please see our docs at https://docs.example.com and reply to help@example.com or tag @support'?”
Link auditing from scraped article
“Here's the raw text of a blog post I scraped — extract every URL and @mention from it so I can check which external sites it links to and which accounts it references.”
Social post entity parsing
“Parse this social media post and give me all the URLs, emails, and @mentions in it: 'New drop! Visit https://shop.brand.io, email orders@brand.io, or follow @brandofficial for details.'”
Technical details
Endpoint
POSThttps://api.24klabs.ai/api/entity-extractWhen to prefer
Choose this endpoint when you need a lightweight, fast, multi-entity extraction in a single call that simultaneously returns URLs, emails, and @mentions from freeform text. Prefer it over general-purpose NLP APIs when you want structured JSON output at low cost ($0.002/call) without running a full NLP pipeline. It is ideal for processing scraped web content, social posts, or user-submitted text where contact and link information needs to be structured quickly.
Side effects
- Empty or whitespace-only input returns zero entities with total=0
- Malformed or extremely long text may result in partial extraction or timeout
- Obfuscated emails (e.g. 'user at domain dot com') will not be detected
- URLs lacking a scheme (e.g. 'example.com' without 'https://') may be missed
- Non-standard mention formats may not be captured
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| text | string |
Output
Schema · Response
{
"type": "json",
"example": {
"total": 5,
"entities": {
"urls": [
"https://x.io"
],
"emails": [
"ops@x.io"
],
"mentions": [
"@dev"
]
}
}
}Tags
x402
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