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Arch Tools — Extract Entities
x402
Arch Tools — Extract Entities is a paid API for AI agents from archtools.dev, paid per call via x402, $0.015/call, status unknown (last checked 2026-09-14).
Extracts named entities (people, organizations, locations, dates, etc.) from a given text string
Price / call$0.015
Success—
StatusUnknown
How this service works
Arch Tools — extract-entities
Output
A JSON object containing the extracted entities found in the input text, including entity values and their types (e.g. PERSON, ORG, GPE, DATE). The exact structure may include entity spans, labels, and confidence scores depending on the service implementation.
Example use cases
News article entity extraction
“Pull out every person, company, and location mentioned in this news article: 'Elon Musk's Tesla announced a new Gigafactory partnership with the German government in Berlin last Tuesday.'”
Legal document entity tagging
“I need to identify all the parties, dates, and jurisdictions mentioned in this contract clause — can you extract the entities from it? Here's the text: 'The agreement between Acme Corp and BrightStart LLC was signed on March 3, 2023, and is governed by the laws of Delaware.'”
CRM enrichment from email body
“Extract the names, company names, and any dates from this email so I can update our CRM: 'Hi, this is Sarah Johnson from TechNova Inc. — could we schedule a call for next Wednesday the 12th?'”
Technical details
Endpoint
POSThttps://archtools.dev/v1/tools/extract-entitiesWhen to prefer
Choose this endpoint when you need fast, per-call named entity recognition on unstructured text without setting up your own NLP pipeline. It is particularly useful in agent workflows where text arrives dynamically and needs to be parsed for structured entities before further processing. At $0.015 per call it is cost-effective for moderate volumes. Prefer it over building custom NER when speed of integration matters.
Side effects
- Empty or missing 'text' field returns a validation error
- Extremely long text may time out or be truncated
- Ambiguous or highly colloquial text may result in missed or misclassified entities
- Non-English text may have reduced accuracy or unsupported entity types
- Payment failure via x402/USDC on Base will block the request
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| text | string | Text to extract entities from |
Tags
x402
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