# Onvexia NLP Analyze

> Onvexia NLP Analyze is a paid API for AI agents from onvexia.com, paid per call via x402, $0.002/call, status unknown (last checked 2026-09-17).

Runs NLP analysis on blockchain-related text documents, extracting structured insights from the Onvexia corpus of half a million analysed crypto documents across ten chains.

## Facts

- Endpoint: POST https://onvexia.com/v1/nlp/analyze
- Price: $0.002/call
- Payment: x402
- Status: unknown
- Last checked: 2026-09-17
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/onvexia-nlp-analyze-970b0dad
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_vi1c0h7cbJ9UaOPYVs4cN

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 onvexia-nlp-analyze-970b0dad -d '<json body>'
```

Example prompt: Can you run Onvexia's NLP analysis on this Ethereum project announcement and pull out the key entities, sentiment, and any labelled address references from their document corpus?

## When to prefer this

Choose this endpoint when you need NLP-based extraction or classification on blockchain and crypto-related text and want to leverage Onvexia's proprietary corpus of half a million analysed documents with labelled addresses and multi-chain supply-age history dating to 2008. It is particularly valuable when you need document-grounded insights rather than raw on-chain data queries, and when your input is free-form text rather than structured blockchain parameters.

## Known failure modes

- Malformed or empty `properties` string returns empty `data` array
- Input referencing assets not in the ten-chain corpus may yield sparse results
- Insufficient USDC balance (x402 payment failure) blocks the call
- Rate limiting or network errors return non-200 HTTP responses
- Ambiguous or very short text inputs may produce low-confidence or empty extractions

## How this service works

Thousands of assets across ten chains, half a million analysed documents, labelled addresses and supply-age history reaching back to 2008 — fused into one reading per asset. REST, SQL, GraphQL and MCP.

## Output

Returns a JSON object with a `data` array containing NLP analysis results (entities, labels, classifications, or extracted signals depending on input) and a `meta` object with documentation links and the endpoint path. The exact structure of data items depends on the properties passed; refer to the OpenAPI spec at onvexia.com/openapi.json for full schema.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "properties": {
   "type": "string"
  }
 }
}
```

## Response schema (JSON Schema)

```json
{
 "type": "json",
 "example": {
  "data": [],
  "meta": {
   "docs": "https://onvexia.com/openapi.json",
   "endpoint": "/v1/nlp/analyze"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/onvexia-nlp-analyze-970b0dad/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from onvexia.com](https://www.zero.xyz/host/onvexia.com/llms.txt)