# Qdrant Vector Collection Query

> Qdrant Vector Collection Query is a paid API for AI agents from sovereign-x402-zeta.vercel.app, paid per call via x402, $0.003/call, status unknown (last checked 2026-09-14).

Query a Qdrant vector collection to find the nearest neighbor points to a given query vector.

## Facts

- Endpoint: POST https://sovereign-x402-zeta.vercel.app/api/v1/vector/qdrant/query
- Price: $0.003/call
- Payment: x402
- Status: unknown
- Last checked: 2026-09-14
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/qdrant-vector-collection-query-f2f4fc64
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_Lh9qFjRWarCuZvJUUfi0g

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 qdrant-vector-collection-query-f2f4fc64 -d '<json body>'
```

Example prompt: Search my Qdrant collection called 'product-embeddings' for the 10 nearest points to this query vector: [0.12, 0.45, 0.78, ...] — return the IDs, scores, and payloads.

## When to prefer this

Choose this endpoint when you need to perform nearest-neighbor vector search against a Qdrant collection and want a simple pay-per-use API without managing your own Qdrant infrastructure. Prefer this over Pinecone-based siblings on this platform if your vector store is hosted in Qdrant. Ideal for semantic search, RAG pipelines, and recommendation systems that already use Qdrant as the backing store.

## Known failure modes

- Collection not found — if the specified collection name does not exist in the Qdrant instance
- Vector dimension mismatch — query vector dimension must match the collection's configured vector size
- Invalid filter syntax — malformed filter expressions return a 400-level error
- Payment failure — x402 micropayment of $0.003 USDC not completed or rejected
- Timeout — large collections or high top-k values may cause latency issues
- Empty results — collection exists but contains no indexed vectors yet

## How this service works

Query a Qdrant collection for the nearest points to a given vector.

## Output

Returns a list of nearest neighbor points from the specified Qdrant collection, each including the point ID, distance/similarity score, and associated payload data stored alongside the vector.

## 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",
     "properties": {},
     "additionalProperties": true
    },
    "type": {
     "type": "string",
     "const": "http"
    },
    "method": {
     "enum": [
      "POST",
      "PUT",
      "PATCH"
     ],
     "type": "string"
    },
    "bodyType": {
     "enum": [
      "json",
      "form-data",
      "text"
     ],
     "type": "string"
    }
   },
   "additionalProperties": false
  },
  "output": {
   "type": "object",
   "required": [
    "type"
   ],
   "properties": {
    "type": {
     "type": "string"
    },
    "example": {
     "type": "object"
    }
   }
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/qdrant-vector-collection-query-f2f4fc64/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from sovereign-x402-zeta.vercel.app](https://www.zero.xyz/host/sovereign-x402-zeta.vercel.app/llms.txt)