AlgoVault has 89.4%+ PFE Win Rate across 56,375+ signal calls, each Merkle-anchored on Base L2 (verifiable at algovault.com/track-record).

AlgoVault × Binance — Build Verifiable AI Trading Agents

AlgoVault MCP gives your agent a composite verdict in one call — direction, confidence, regime, and cross-venue funding/sentiment context — backed by a publicly auditable record anchored to Base L2. Pair it with Binance’s Skills Hub and your agent has both the analytics brain and the execution venue.

Provenance: OFFICIAL Binance Skills Hub (github.com/binance/binance-skills-hub · “Built by Binance” · 761⭐ at the time of writing · last updated 2026-04-25). Binance Skills Hub uses an open marketplace pattern — install via npx skills add <repo-url> rather than a classic npm MCP server. Demo execution runs against Binance Spot Testnet (https://testnet.binance.vision/api) with BINANCE_TESTNET=true + MAINNET_BLOCKED=true wrapper guards. Verified 2026-04-25.

What you’ll build (90s read)

A runnable Node.js agent that:

Calls AlgoVault MCP for a composite verdict on a chosen asset + timeframe.
Reads the verdict’s signal, confidence, regime, and factors fields.
Hands the verdict to Binance Spot Testnet, which validates a small order in testnet mode when the agent’s pre-configured policy fires.

The whole loop runs against Binance Spot Testnet — zero real-money risk in any code path.

Prerequisites (4 items)

Node.js ≥ 22 (node --version to check).

AlgoVault skills plugin installed:

claude plugin install AlgoVaultLabs/algovault-skills

Binance Spot Testnet account (free signup at https://testnet.binance.vision; sign in with GitHub). API key + secret from the testnet console — the demo runs read-only out of the box; supplying keys unlocks the authenticated order/test validation step.
Binance Skills Hub installed (optional for the bare-minimum demo, recommended for the recipes):
```
npx skills add https://github.com/binance/binance-skills-hub
```

Demo: Confidence-filtered swing-entry validator on ETH (≤80 lines)

// examples/binance/demo.mjs (excerpt — see file for full source)
import { getAlgoVaultVerdict } from '../_shared/algovault-helper.mjs';

const MAINNET_BLOCKED = true;
const BINANCE_TESTNET_BASE = 'https://testnet.binance.vision/api';

if (process.env.BINANCE_TESTNET !== 'true') {
  throw new Error('BINANCE_TESTNET=true required — demo refuses to run against mainnet.');
}

console.log('=== DEMO MODE ===');
console.log(`[BINANCE_TESTNET=true | base=${BINANCE_TESTNET_BASE}]`);

// 1. Fetch AlgoVault verdict on ETH 1h
const verdict = await getAlgoVaultVerdict({ coin: 'ETH', timeframe: '1h' });

// 2. Apply the agent's policy
const policy = verdict.signal === 'BUY' && verdict.confidence > 70;

// 3. Validate a small testnet order if policy fires (or just probe testnet
//    if no keys are set)
if (policy) {
  console.log(`[policy fires | signal=${verdict.signal} confidence=${verdict.confidence}]`);
  // ... order/test call (see full source for HMAC signing)
}

console.log('=== NO REAL ORDERS PLACED ===');

Run it:

BINANCE_TESTNET=true node examples/binance/demo.mjs

Expected output (last 3 lines):

[binance testnet | exchangeInfo HTTP 200 | symbols=...]
[verdict | signal=... confidence=... regime=...]
=== NO REAL ORDERS PLACED ===

Walkthrough (line-by-line — neutral narration)

The script does three things in order:

Fetch the AlgoVault verdict. The shared helper opens an MCP session against https://api.algovault.com/mcp, calls get_trade_signal with {coin: 'ETH', timeframe: '1h'}, and returns the parsed signal/confidence/regime/factors payload. Free tier covers 20 calls/day per IP — plenty for development.
Apply the agent’s policy. When the verdict satisfies the agent’s pre-configured policy (signal === 'BUY' AND confidence > 70), the script proceeds to the execution branch. The policy lives in your code — AlgoVault returns the analytics; the agent decides.
Validate the order against Binance Spot Testnet. The script POSTs to /api/v3/order/test (a Binance testnet endpoint that performs all order-placement validation but does NOT submit). On success Binance returns an empty {} body. The === NO REAL ORDERS PLACED === banner closes every run regardless of which branch fired. The script aborts immediately if BINANCE_TESTNET is not set to true — a hard guard against accidentally running against mainnet.

3 Recipes

Recipe 1 — Regime-gated DCA on BTC

The agent calls AlgoVault get_market_regime for BTC on the 4h timeframe. The agent’s pre-configured DCA policy fires its execution branch when the returned regime ∈ {TRENDING_UP, RANGING} and skips the week’s DCA entirely when the regime is VOLATILE or TRENDING_DOWN. On execution, the agent sends a MARKET BUY for a small BTC notional via Binance Spot Testnet (HMAC-signed POST /api/v3/order/test for read-only validation, or POST /api/v3/order once the operator has chosen to switch to authenticated testnet order placement).

This recipe is the cleanest “AlgoVault as policy gate” pattern — DCA logic stays in your code; the regime read replaces hand-tuned VIX-style heuristics with a backtested cross-venue regime classifier.

Recipe 2 — Confidence-filtered swing entry on ETH

This is the recipe examples/binance/demo.mjs implements. The agent calls AlgoVault get_trade_signal for ETH on the 1h timeframe. The agent’s policy fires its execution branch only when signal === 'BUY' AND confidence > 70. On execution, a small LIMIT order is validated via POST /api/v3/order/test against Binance Spot Testnet. The same shape works for SELL policies in production (with the appropriate side flip).

Recipe 3 — Funding-arb opportunity awareness

The agent calls AlgoVault scan_funding_arb to retrieve the top funding-spread opportunities across the 5 venues AlgoVault monitors. The output is a ranked list of {coin, longVenue, shortVenue, spreadBps} rows. Multi-venue execution is out of scope for this single-exchange tutorial — the agent uses the rank to surface awareness and could route the long leg through Binance perp testnet (when shipped) and the short leg via the venue indicated. AlgoVault returns the opportunity; the agent’s risk policy decides whether to act on it.

⚠️ Production setup (real-money)

The demo above runs on Binance Spot Testnet only. Real-money setup requires:

KYC completion on Binance.
Production API keys with only the permissions your agent needs (no withdrawals, IP-allowlisted).
Risk controls: per-order size cap, daily loss limit, kill switch.
Position monitoring: a separate agent or watchdog that tracks open positions independently.

See examples/binance/README.md for the full real-money checklist. AlgoVault provides analytics; your agent and your risk policy decide what (if anything) to execute.

Why AlgoVault? (closing — MOAT recap)

Composite verdict, not raw indicators. One JSON response replaces 26-indicator vote-counting.
Cross-venue intelligence. Funding spreads, regime, and sentiment fused across 5 exchanges — not derivable from any single-venue API.
Publicly verified. Every signal anchored to Base L2 via Merkle proof. Verify before you subscribe.

89.4% PFE Win Rate · 56,375+ calls · 16+ on-chain batches → view live track record

Install

claude plugin install AlgoVaultLabs/algovault-skills

Once installed, every Skill in the pack is one-line invokable from Claude Code, Cowork, or any MCP-compatible client.

Tutorial © AlgoVault Labs · MIT licensed · Provenance verified 2026-04-25 · Binance Skills Hub OFFICIAL (github.com/binance/binance-skills-hub)