# Text Embedding API (768-dim)

> Text Embedding API (768-dim) is a paid API for AI agents from released-mph-process-lib.trycloudflare.com, paid per call via x402, $0.005/call, status unknown (last checked 2026-10-20).

Converts input text or arrays of text into 768-dimensional vector embeddings for semantic similarity, search, and classification tasks.

## Facts

- Endpoint: POST https://released-mph-process-lib.trycloudflare.com/v1/embed?utm_source=zero.xyz
- Price: $0.005/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-20
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/text-embedding-api-768-dim-1f89a459
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_8MNuW8HLaJW6HjVAN_Jja

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 text-embedding-api-768-dim-1f89a459 -d '<json body>'
```

Example prompt: Can you embed this sentence into a 768-dimensional vector: 'The quick brown fox jumps over the lazy dog'?

## When to prefer this

Choose this endpoint when you need fast, affordable 768-dimensional text embeddings via a simple REST call with per-call micropayment pricing ($0.005 USDC). Ideal for agents that need to embed text on-the-fly without managing API keys or subscriptions, especially in agentic pipelines using the x402 payment protocol.

## Known failure modes

- Empty or null input string returns an error
- Input array exceeds maximum batch size limit
- Network timeout if input text is extremely long
- Payment failure via x402 protocol blocks the request
- Malformed JSON body returns 400 error

## How this service works

Text embeddings (768-dim). Send {"input": "text"} or {"input": ["a","b"]}.

## Output

Returns a 768-dimensional floating-point vector (or array of vectors for batch input) representing the semantic content of the input text, suitable for similarity comparison, nearest-neighbor search, or downstream ML tasks.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "usage": {
   "type": "object"
  },
  "choices": {
   "type": "array"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/text-embedding-api-768-dim-1f89a459/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from released-mph-process-lib.trycloudflare.com](https://www.zero.xyz/host/released-mph-process-lib.trycloudflare.com/llms.txt)