ManyLives Vector Memory Add

x402

ManyLives Vector Memory Add is a paid API for AI agents from api.manylives.me, paid per call via x402, $0.003/call, status unknown (last checked 2026-10-10).

Stores text items with optional metadata into a named vector memory namespace for later semantic retrieval by AI agents

Price / call$0.003

Seller volume →—

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

Returns a JSON object with the list of stored item IDs (including auto-generated ones for items without an explicit ID), total items stored in this call, total items in the wallet/namespace, the namespace name, and the storage limit (max 2,000 items).

Example use cases

Trading agent research memory

“Add this to my trading agent's memory in the 'market-analysis' namespace: 'BTC dominance broke above 55% on high volume, historically precedes altcoin pullback.' Tag it with source 'on-chain' and ID 'btc-dom-note-2024'.”

Supplier negotiation notes store

“Store these three supplier quotes in my vector memory under the namespace 'procurement': first, ID 'sup-a': 'Supplier A quoted $12 per unit for 1000 units, net 30 terms'; second, ID 'sup-b': 'Supplier B quoted $10.50 per unit, requires prepayment'; third, ID 'sup-c': 'Supplier C offered volume discounts above 2000 units'.”

Agent observation logging

“My agent just observed something important — save it to the 'agent-logs' namespace: 'User expressed strong risk aversion during portfolio review, prefers max 5% drawdown strategies.' Use ID 'obs-risk-001' and tag it with source 'conversation'.”

Technical details

Endpoint

POSThttps://api.manylives.me/paid/memory/vector-add?utm_source=zero.xyz

When to prefer

Use this endpoint when an AI agent needs persistent, semantically searchable memory across sessions — especially for trading agents building up notes, observations, or research over time. Prefer this over plain key-value stores when the content will later be retrieved by semantic similarity rather than exact key lookup. Ideal for agents that need to accumulate knowledge incrementally and upsert entries by ID without duplicating data.

Side effects

Text exceeds 4,000 character limit per item — request rejected
Namespace not found or invalid — defaults to 'default' namespace
Storage limit of 2,000 items reached — further adds rejected
Payment not included or insufficient USDC — 402 response returned
Malformed items array — 400 validation error
Item ID collision with incompatible schema — upsert may overwrite existing item

Input

Schema · Request body

Field	Type	Description
items	string	array of {text (required, max 4,000 chars), id (optional, reuse to update), meta (optional JSON)}
namespace	string	optional group name (default 'default')

Output

Schema · Response

{
  "type": "json",
  "example": {
    "ids": [
      "note-1",
      "v_k3m8q2r7t9w4"
    ],
    "limit": 2000,
    "stored": 2,
    "namespace": "default",
    "items_in_wallet": 2
  }
}

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