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AWS Bedrock Embeddings API (x402)
x402
AWS Bedrock Embeddings API (x402) is a paid API for AI agents from aws-bedrock-agent-api.vercel.app, paid per call via x402, $0.005/call, status unknown (last checked 2026-10-12).
Converts text or batches of text into vector embeddings using Amazon Bedrock models, accessible via pay-per-call with USDC micropayments.
Price / call$0.005
Success—
StatusUnknown
How this service works
Pay-per-call Amazon Bedrock proxy on x402 and MPP.
Output
Returns dense vector embeddings (floating-point arrays) representing the semantic content of the input text(s). Each input string maps to one embedding vector usable for similarity search, clustering, classification, or retrieval-augmented generation.
Example use cases
Semantic search index ingestion
“Take these 10 product descriptions and embed them all using the AWS Bedrock Titan model so I can store them in my vector database for semantic search.”
RAG pipeline document encoding
“I'm building a retrieval-augmented generation system — can you embed this paragraph using the Bedrock embedding model so I can match it against user queries later?”
Text similarity scoring
“Embed both of these two customer reviews using the AWS Bedrock embedding model so I can compare their vector similarity and see how related they are.”
Technical details
Endpoint
POSThttps://aws-bedrock-agent-api.vercel.app/api/embeddings?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need text embeddings from Amazon Bedrock models (e.g. Titan Embeddings) without managing your own AWS credentials or infrastructure, and you want pay-per-call micropayment billing via USDC/x402 rather than a subscription. Ideal for agents that need on-demand embeddings for RAG pipelines, semantic search, or similarity tasks.
Side effects
- Invalid or unsupported model name returns an error — use GET /api/models to list valid options
- Empty string input rejected due to minLength:1 constraint
- Batch exceeding 64 items rejected due to maxItems:64 constraint
- Payment failure or insufficient USDC balance blocks the request
- Malformed input schema (wrong type) returns a validation error
- Network timeout if the upstream Bedrock model is slow to respond
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| input | — | Text or list of texts to embed |
| model | string | Azure embedding deployment from GET /api/models. |
Tags
x402
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