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ManyLives AI Text Embedding
x402
ManyLives AI Text Embedding is a paid API for AI agents from api.manylives.me, paid per call via x402, $0.002/call, status unknown (last checked 2026-10-10).
Converts one or more text strings into 1024-dimensional BGE-M3 semantic embedding vectors, billed per call via USDC micropayment on Base.
Price / call$0.002
Success—
StatusUnknown
How this service works
Pay-per-call tools for people building AI agents: live web search and page contents, point-in-time crypto market data and news for backtests (no lookahead), verifiable track records of 1,000 crypto strategies locked on the Base network, company profiles, quick AI and batch prices. Ask us to turn a public website into a JSON endpoint. Pay per call, no account, free trial.
Output
A JSON object containing: the count of embedded texts, the model name ('bge-m3'), an array of float arrays (one per input text) each of 1024 dimensions, and the dimension count. Vectors are unit-normalized by default.
Example use cases
RAG pipeline for trading strategies
“Embed this strategy description so I can store it in a vector database and retrieve similar strategies later: 'RSI divergence with volume confirmation on BTC 4h chart, long only, 2% stop loss.'”
Semantic similarity search across agent marketplace
“I need embedding vectors for these three agent capability descriptions — 'on-chain risk monitor', 'verifiable backtest runner', 'portfolio rebalancer' — so I can find the most semantically similar agents in the ManyLives marketplace.”
Clustering user queries by intent
“Convert these five user questions into BGE-M3 vectors with unit normalization so I can cluster them by topic: 'what is my drawdown?', 'show me profitable strategies', 'which coins are trending?', 'backtest this signal', 'compare Sharpe ratios.'”
Technical details
Endpoint
POSThttps://api.manylives.me/paid/ai/embed?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need pay-per-call text embeddings with no account setup, billed in USDC micropayments on Base, especially within the ManyLives trading agent ecosystem where embeddings are used alongside verifiable backtests, market data, and on-chain tools. Prefer it over hosted embedding APIs that require subscriptions when you want frictionless per-call billing for autonomous AI agents.
Side effects
- Payment not included or insufficient USDC — returns HTTP 402 Payment Required
- texts field missing or empty — returns validation error
- Input too long for model context window — may return truncation error or 400
- Network or model inference timeout — returns 5xx error
- Malformed JSON body — returns 400 Bad Request
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| texts | string | array of strings (or text: one string) |
| normalize | string | optional true (default) for unit-length vectors |
Output
Schema · Response
{
"type": "json",
"example": {
"count": 2,
"model": "bge-m3",
"vectors": [
[
0.0123,
-0.0456,
"…"
],
[
0.0211,
0.0034,
"…"
]
],
"dimensions": 1024
}
}Tags
x402
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