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AllTheBot Keywords & Entities Extractor
x402
AllTheBot Keywords & Entities Extractor is a paid API for AI agents from velux.taild4d007.ts.net:8443, paid per call via x402, $0.007/call, status unknown (last checked 2026-10-10).
Extracts named entities (people, organizations, locations, etc.) and keywords from a block of text using AI
Price / call$0.007
Success—
StatusUnknown
How this service works
Keyword extraction and named entity recognition (NER): people, organizations, locations, dates, money, products. Any language, JSON output.
Output
A JSON object with two fields: 'entities' (an array of objects each containing 'text' and 'type' such as organization, person, or location) and 'keywords' (an array of keyword strings found in the input text).
Example use cases
Entity tagging for news articles
“Extract all the people, organizations, and locations mentioned in this paragraph from a Reuters article: 'Apple CEO Tim Cook met with European Commission President Ursula von der Leyen in Brussels to discuss digital market regulations.'”
Keyword extraction for SEO analysis
“What are the main keywords and named entities in this product description I want to optimize for search: 'The new Tesla Model S Plaid features a tri-motor all-wheel-drive system developed at the Fremont factory in California.'”
Contract party identification
“Identify all organizations and key terms in this contract clause: 'This agreement is entered into between Goldman Sachs Group Inc., a Delaware corporation, and Stripe Inc., headquartered in San Francisco, California.'”
Technical details
Endpoint
GEThttps://velux.taild4d007.ts.net:8443/x402/entities?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to extract structured named entities (with type labels) and keywords from unstructured text in a single low-cost call ($0.007 USDC), without needing an API key or account setup. Ideal for agents that process news, documents, or user-generated content and need to identify key actors, organizations, or topics on-demand. Prefer over heavier NLP pipelines when speed, cost, and zero-setup are priorities.
Side effects
- Text exceeds 6000 character limit — request rejected or truncated
- Ambiguous or very short text may yield empty entities and keywords arrays
- Payment failure in USDC on Base will result in 402 error before processing
- Non-English or mixed-language text may produce lower-quality entity recognition
- Highly domain-specific jargon may not be recognized as named entities
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Output
Schema · Response
{
"type": "json",
"example": {
"result": {
"entities": [
{
"text": "Airbus",
"type": "organization"
}
],
"keywords": [
"Airbus"
]
}
}
}Tags
x402
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