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CortexCloud Text Embedding API
x402
CortexCloud Text Embedding API is a paid API for AI agents from api.cortexcloud.org, paid per call via x402, $0.004/call, status unknown (last checked 2026-09-14).
Generates vector embeddings for one or more text strings using configurable embedding models, paid per call in USDC via x402
Price / call$0.004
Success—
StatusUnknown
How this service works
One pay-per-call API for AI agents: optimization, AI, research, on-chain data, and automation — all settled in USDC on Base via x402. Discover via MCP and Bazaar, estimate free, pay per call. No API keys, no signup.
Output
Returns a JSON object containing an array of embedding objects (each with a float array 'embedding'), the model name used (e.g. 'openrouter/google/text-embedding-004'), and the price in USD for the call. Each input string maps to one embedding vector in the data array.
Example use cases
RAG pipeline document ingestion
“Embed these 5 product descriptions so I can index them in my vector store for semantic search: 'Wireless noise-cancelling headphones with 30hr battery', 'Ergonomic standing desk with height memory presets', 'Mechanical keyboard with RGB backlighting', 'Ultra-wide curved gaming monitor 34 inch', 'Portable Bluetooth speaker waterproof IPX7'.”
Semantic similarity scoring
“Turn these two user reviews into embedding vectors so I can measure how similar they are: 'Absolutely loved the fast shipping and quality packaging' and 'Delivery was quick and the product arrived in perfect condition'.”
Query embedding for vector search
“Convert this search query into a vector embedding using text-embedding-004 so I can run a nearest-neighbor lookup against my knowledge base: 'how do I reset my account password?'”
Technical details
Endpoint
GEThttps://api.cortexcloud.org/v1/ai/embedWhen to prefer
Choose this endpoint when you need pay-per-call text embeddings with no API key or account signup, settling payment in USDC on Base via x402. Ideal for autonomous AI agents that need to embed text on demand without managing subscription billing. Prefer this over OpenAI or Cohere direct APIs when operating in a crypto-native, agent-to-agent payment context or when you want cost transparency at the per-call level.
Side effects
- Input array exceeds 128 items — returns error indicating maxItems constraint
- Empty input array (minItems: 1 violation) — returns validation error
- Invalid model name — may return error or fall back to default
- Payment failure via x402 — 402 response if USDC payment not completed
- Oversized individual strings may cause token limit errors from underlying model
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| input | array | |
| model | string |
Output
Schema · Response
{
"type": "object",
"format": "application/json",
"example": {
"data": [
{
"embedding": [
0.01,
0.02,
-0.03
]
}
],
"model": "openrouter/google/text-embedding-004",
"price_usd": 0.0001
}
}Tags
x402
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