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CortexCloud Embeddings
x402
CortexCloud Embeddings is a paid API for AI agents from api.cortexcloud.org, paid per call via x402, $0.005/call, status unknown (last checked 2026-09-14).
Generates vector embeddings for a given text string using a specified embedding model, billed per call in USDC via x402.
Price / call$0.005
Success—
StatusUnknown
How this service works
OpenAI-compatible AI and data API for agents. Pay per call in USDC on Base via x402 — no API keys, no subscriptions, no lock-in.
Output
Returns a JSON object containing a 'data' array of embedding vectors (each an array of floats), the 'model' name used, and an 'object' field indicating the response type. The embedding array can be used directly for cosine similarity, nearest-neighbor search, or storage in a vector database.
Example use cases
Semantic search index builder
“Take this product description — 'Lightweight waterproof hiking boots with ankle support' — and convert it to a vector embedding using gemini/text-embedding-004 so I can store it in my semantic search index.”
RAG pipeline query vectorization
“I need to embed this user question before doing a similarity lookup in my vector database: 'What is the return policy for online orders?' Use the text-embedding-004 model.”
Document similarity clustering
“Embed this customer review — 'The battery life is excellent but the screen is dim in sunlight' — with gemini/text-embedding-004 so I can cluster it with similar feedback.”
Technical details
Endpoint
GEThttps://api.cortexcloud.org/x402/v1/embeddingsWhen to prefer
Choose this endpoint when you need a pay-per-call embedding service with no API key management or subscription overhead, particularly in agent workflows that require dynamic, metered access. It is especially useful for AI agents operating autonomously with crypto wallets, needing OpenAI-compatible embedding outputs from multiple underlying providers (e.g. Gemini) without vendor lock-in.
Side effects
- Missing or empty 'input' field returns a 400 validation error
- Invalid or unsupported model ID may return a 400 or 404 error
- Insufficient USDC balance or failed x402 payment results in a 402 Payment Required response
- Network timeout for large input texts
- Rate limiting if too many requests are sent in rapid succession
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| input | string | Text to embed |
| model | string | Embedding model id, e.g. gemini/text-embedding-004 |
Output
Schema · Response
{
"type": "object",
"format": "application/json",
"example": {
"id": "emb_abc",
"data": [
{
"index": 0,
"object": "embedding",
"embedding": []
}
],
"usage": {
"total_tokens": 0,
"prompt_tokens": 0
},
"object": "list"
}
}Tags
x402
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