# AUBRAI Encrypted Literature Query (x402)

> AUBRAI Encrypted Literature Query (x402) is a paid API for AI agents from x402.aubr.ai, paid per call via x402, $0.03/call, status unknown (last checked 2026-09-14).

Accepts an HPKE-encrypted longevity/aging science query and returns a poll URL for async results from an AI science agent backed by biomedical literature

## Facts

- Endpoint: GET https://x402.aubr.ai/api/literature/encrypted
- Price: $0.03/call
- Payment: x402
- Status: unknown
- Last checked: 2026-09-14
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/aubrai-encrypted-literature-query-x402-c7a9726f
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_BnGgxyEVlWkoZ03XhJydS

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 aubrai-encrypted-literature-query-x402-c7a9726f
```

Example prompt: Using the AUBRAI science agent, find me evidence-based research on whether senolytics like navitoclax can extend healthy lifespan — I want citations from recent papers and a clear summary of what the science currently says.

## When to prefer this

Choose this endpoint when you need privacy-preserving (end-to-end encrypted) queries to a specialized longevity and aging science AI agent that returns evidence-based answers with direct citations from biomedical literature. Prefer over general LLM queries when you need grounded citations and an agent specifically trained on aging/geroscience research. The HPKE encryption makes it suitable for sensitive research queries.

## Known failure modes

- Invalid or malformed HPKE ciphertext returns decryption error
- Missing hpke_ephemeral_public_key causes 400 bad request
- Payment not included or insufficient (x402 payment required)
- Poll URL returns pending indefinitely if backend times out
- Base64 encoding errors cause parameter rejection

## How this service works

Aubrai is an AI science agent inspired by Dr. Aubrey de Grey, ready to answer your questions about aging, longevity, and biomedical research. Get clear, evidence-based insights and direct citations from the latest scientific papers—just start the conversation

## Output

A JSON object with a 'status' field (e.g. 'pending'), a 'requestId' string, and a 'pollUrl' path the agent should poll to retrieve the actual AI-generated scientific answer with citations once processing completes.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "hpke_ciphertext": {
   "type": "string",
   "description": "HPKE-encrypted literature query, base64-encoded"
  },
  "hpke_ephemeral_public_key": {
   "type": "string",
   "description": "Sender's one-time X25519 public key, base64-encoded"
  }
 }
}
```

## Response schema (JSON Schema)

```json
{
 "type": "json",
 "example": {
  "status": "pending",
  "pollUrl": "/api/literature/encrypted/status/req_abc123",
  "requestId": "req_abc123"
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/aubrai-encrypted-literature-query-x402-c7a9726f/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from x402.aubr.ai](https://www.zero.xyz/host/x402.aubr.ai/llms.txt)