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NetIntel Text Embeddings
x402
NetIntel Text Embeddings is a paid API for AI agents from netintel.dev, paid per call via x402, $0.005/call, status unknown (last checked 2026-09-15).
Generate vector embeddings for text using OpenAI's text-embedding-3-small model, paid per-call via x402 micropayments with no API key required
Price / call$0.005
Success—
StatusUnknown
How this service works
OpenAI-compatible text embeddings API (alias of /v1/embeddings for api/v1-style base URLs) — input as a string or batch of up to 128 strings, model text-embedding-3-small (default) or text-embedding-3-large. Flat $0.005 per call in USDC via x402, no OpenAI account or API key.
Output
Returns a JSON object containing a list of embedding objects, each with an index, object type, and a float array representing the vector embedding; also includes the model name used (text-embedding-3-small) and token usage stats (prompt_tokens, total_tokens).
Example use cases
Example prompt
“Turn this text into an embedding vector for me: 'The quick brown fox jumps over the lazy dog' — I need the float array I can store in my vector database.”
Technical details
Endpoint
POSThttps://netintel.dev/api/v1/embeddingsWhen to prefer
Choose this endpoint when you need text embeddings on a pay-per-call basis with no API key or account signup — ideal for agents making sporadic embedding calls, prototyping semantic search pipelines, or operating in environments where managing OpenAI credentials is impractical. Particularly useful when you want guaranteed no-charge on failures, making it safe for automated retry logic.
Side effects
- Invalid or empty input text returns a validation error with no charge
- Upstream OpenAI service failure returns a server error with no charge billed
- Insufficient USDC balance or x402 payment failure blocks the call
- Malformed request body returns an input-validation rejection at no cost
- Rate limiting or quota exhaustion on the upstream model provider
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Output
Schema · Response
{
"type": "json",
"example": {
"data": [
{
"index": 0,
"object": "embedding",
"embedding": [
0.0102,
-0.0083,
0.0264
]
}
],
"model": "text-embedding-3-small",
"usage": {
"total_tokens": 4,
"prompt_tokens": 4
},
"object": "list"
}
}Tags
x402
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