Index onlineMerchant portal
Api Endpoint

Quartermaster Embeddings

Text embeddings for semantic search and RAG: one vector per call, 1024 dimensions.

Open interactive test console

Offering

Provider
quartermaster.surewhynot.app
Method
GET
Offering type
Api Endpoint
Transport type
http
Category
Development
Delivery
Not provided
Pricing model
Not provided
x402 version
2

Endpoint context

URL
https://quartermaster.surewhynot.app/v1/embed
MIME type
application/json
First seen
2026-10-16T01:50:06.715Z
Last seen
Tags
AI, embeddings, vectors, RAG, semantic-search, Agents

Website

Payment pricing

x402 payment terms are the authoritative price for calling this endpoint.

Payment option 1
0.002 USDC
Atomic price: 2000 · Network: eip155:8453 · Asset: USDC · Scheme: exact
Payment option 2
0.002 USDC
Atomic price: 2000 · Network: solana:5eykt4UsFv8P8NJdTREpY1vzqKqZKvdp · Asset: USDC · Scheme: exact
Raw x402 terms
[
  {
    "scheme": "exact",
    "network": "eip155:8453",
    "asset": "0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913",
    "amount": "2000",
    "payTo": "0x5253666c40432f009ebd99908b9cd2a7fd1019cb"
  },
  {
    "scheme": "exact",
    "network": "solana:5eykt4UsFv8P8NJdTREpY1vzqKqZKvdp",
    "asset": "EPjFWdd5AufqSSqeM2qN1xzybapC8G4wEGGkZwyTDt1v",
    "amount": "2000",
    "payTo": "FgcKNzsBXSEHGNZNWetPsjXiBZk1WFoU6sF2zVsnzXfa"
  }
]

Observed health

Status
Healthy
Latest latency
1229 ms
Average latency
933 ms
HTTP status
402
Last checked
Reachability
100% over 14 checks

Latency is measured to the first response headers. A reachable result does not verify response accuracy or merchant identity.

Input schema

{
  "type": "object",
  "properties": {
    "type": {
      "type": "string",
      "const": "http"
    },
    "method": {
      "type": "string",
      "enum": [
        "GET"
      ]
    },
    "queryParams": {
      "type": "object",
      "properties": {
        "text": {
          "type": "string",
          "maxLength": 8000,
          "description": "Text to embed"
        }
      },
      "required": [
        "text"
      ]
    }
  },
  "required": [
    "type",
    "method"
  ],
  "additionalProperties": false
}

Output schema

{
  "type": "json",
  "example": {
    "model": "@cf/qwen/qwen3-embedding-0.6b",
    "embedding": [
      0.0123,
      -0.0456
    ],
    "dimensions": 1024
  }
}