# NetIntel Text Embeddings

> 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

## Facts

- Endpoint: POST https://netintel.dev/api/v1/embeddings
- Price: $0.005/call
- Payment: x402
- Status: unknown
- Last checked: 2026-09-15
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/netintel-text-embeddings-8f434067
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_BfOiso21_qoYB2wknnW3v

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 netintel-text-embeddings-8f434067 -d '<json body>'
```

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.

## When to prefer this

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.

## Known failure modes

- 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

## 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).

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "$schema": "https://json-schema.org/draft/2020-12/schema",
 "required": [
  "input"
 ],
 "properties": {
  "input": {
   "type": "object",
   "required": [
    "type",
    "method",
    "bodyType",
    "body"
   ],
   "properties": {
    "body": {
     "type": "object",
     "required": [
      "input"
     ],
     "properties": {
      "input": {
       "type": "string",
       "description": "Text to embed. Also accepts an array of up to 128 strings (64000 chars total)."
      },
      "model": {
       "type": "string",
       "description": "text-embedding-3-small (default) or text-embedding-3-large"
      },
      "dimensions": {
       "type": "number",
       "description": "Optional output vector size (truncation)."
      }
     }
    },
    "type": {
     "type": "string",
     "const": "http"
    },
    "method": {
     "enum": [
      "POST"
     ],
     "type": "string"
    },
    "bodyType": {
     "enum": [
      "json",
      "form-data",
      "text"
     ],
     "type": "string"
    }
   },
   "additionalProperties": false
  },
  "output": {
   "type": "object",
   "required": [
    "type"
   ],
   "properties": {
    "type": {
     "type": "string"
    },
    "example": {
     "type": "object",
     "properties": {
      "data": {
       "type": "array",
       "description": "[{object:'embedding', index, embedding:[…]}]"
      },
      "model": {
       "type": "string"
      },
      "usage": {
       "type": "object"
      },
      "object": {
       "type": "string"
      }
     }
    }
   }
  }
 }
}
```

## Response schema (JSON Schema)

```json
{
 "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"
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/netintel-text-embeddings-8f434067/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from netintel.dev](https://www.zero.xyz/host/netintel.dev/llms.txt)