GEDX402 Vector Upsert

x402

GEDX402 Vector Upsert is a paid API for AI agents from search.gedx402.com, paid per call via x402, $0.02/call, status unknown (last checked 2026-09-15).

Upserts raw embedding vectors into a namespaced vector index, paid per-call with USDC via x402 protocol, no API keys required.

Price / call$0.02

Seller volume →—

Success—

StatusUnknown

How this service works

x402 workers ai. pay with usdc on base, polygon, arbitrum, world, or solana. no api keys.

Output

Returns a JSON object confirming how many vectors were upserted, e.g. {"upserted": 1}. No API key required; payment is handled automatically via x402 USDC on supported chains.

Example use cases

Example prompt

“Store these two 768-dimension embeddings into my 'project-alpha' namespace: first vector with id 'doc-001' and values [0.12, 0.45, ...], second with id 'doc-002' and values [0.33, 0.77, ...], both with metadata {source: 'wiki'}.”

Technical details

Endpoint

GEThttps://search.gedx402.com/v1/vector/upsert

When to prefer

Choose this endpoint when you need to store embedding vectors without managing API keys, want to pay per-call in USDC via x402 on Base, Polygon, Arbitrum, World, or Solana, and require namespace isolation per agent or project. Ideal for serverless RAG pipelines or agent memory systems built on Cloudflare Workers AI with 768-dim embeddings.

Side effects

Invalid vector dimensions (not 768 floats) — likely 422 or 400 error
Namespace too short or too long (must be 2-64 chars) — validation error
Missing required vector id or values fields — 400 bad request
Payment not accepted or insufficient USDC balance — 402 payment required
Vector array is empty — may return upserted: 0 or validation error

Input

Schema · Request body

Field	Type	Description
vectors	array	Raw vectors for upsert (768 dims for default index).
namespace	string	Agent collection id (2-64 chars). Isolates vectors per agent or project.

Output

Schema · Response

{
  "type": "json",
  "example": {
    "upserted": 1
  }
}

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Technical details

Endpoint

GEThttps://search.gedx402.com/v1/vector/upsert

When to prefer

Side effects

Invalid vector dimensions (not 768 floats) — likely 422 or 400 error
Namespace too short or too long (must be 2-64 chars) — validation error
Missing required vector id or values fields — 400 bad request
Payment not accepted or insufficient USDC balance — 402 payment required
Vector array is empty — may return upserted: 0 or validation error

Input

Schema · Request body

Field	Type	Description
vectors	array	Raw vectors for upsert (768 dims for default index).
namespace	string	Agent collection id (2-64 chars). Isolates vectors per agent or project.

Output

Schema · Response

{
  "type": "json",
  "example": {
    "upserted": 1
  }
}