crypto-quant-signal-mcp

crypto-quant-signal-mcp

AI-native quantitative trading signal engine for crypto and TradFi perpetuals. Multi-factor composite BUY/SELL/HOLD signals, cross-venue funding rate arbitrage scanning, and market regime detection powered by Hyperliquid data.

Category
访问服务器

README

<p align="center"> <img src="https://raw.githubusercontent.com/AlgoVaultLabs/crypto-quant-signal-mcp/main/logo.png" alt="AlgoVault" width="120" /> </p>

crypto-quant-signal-mcp

The call intelligence layer for AI trading agents — composite quant calls across 5 exchanges (Hyperliquid, Binance, Bybit, OKX, Bitget), cross-venue arbitrage detection, and regime-aware market classification via MCP.

npm version npm downloads License: MIT On-Chain Verified

Live Track Record — 91%+ directional accuracy across 19,000+ trade calls on 5 exchanges. Public, no login required.


Why AlgoVault

Most MCP trading servers give you raw data — prices, order books, candles. Your agent still has to figure out what to do with it.

AlgoVault is different. We give your agent one answer: a directional verdict with a confidence score, built from a multi-factor composite scoring engine tuned on production quant systems. Every call is tracked, every outcome is measured, and the full track record is public from day one.

What makes this not just another indicator wrapper:

  • Composite scoring, not single-indicator noise. Multiple orthogonal signals — momentum oscillators, trend structure, derivatives positioning, volume dynamics, open interest flow — fused into a single weighted verdict. The weights are calibrated from live market outcome data, not textbook defaults.
  • Regime-aware call generation. Calls are filtered through a market regime classifier before emission. The engine knows when to issue calls and when to stay silent — a trend-following setup in a ranging market gets suppressed, not broadcast.
  • Cross-venue intelligence. Full signal generation on 5 exchanges — Hyperliquid, Binance, Bybit, OKX, and Bitget — with native candle, OI, funding, and volume data per venue. Cross-venue funding arbitrage scanning across all venues. Nobody else does multi-exchange derivatives analysis via MCP.
  • Published track record with every release. Every call is recorded with outcome prices at multiple horizons. Win rate, profit factor, and expected value are computed continuously. No cherry-picking, no survivorship bias.
  • Adaptive scoring. Indicator weights are retuned monthly from outcome data. The engine learns what works and adjusts — the call you get today is better than the one from last month.
  • Crypto + TradFi coverage. 290+ assets across 5 exchanges — standard crypto perps on all venues, TradFi perpetuals (stocks, indices, commodities, FX) on Hyperliquid, and liquidity-filtered meme coins. Assets are classified into quality tiers with per-exchange signal generation.

Try It in 30 Seconds

No code. No API key. No install.

Step 1. Open Claude → Settings → Integrations → Add custom connector

Step 2. Enter the name and URL:

Field Value
Name Crypto Quant Signal
URL https://api.algovault.com/mcp

Add Connector

Step 3. Ask Claude anything:

"Get me a trade signal for ETH on the 4h timeframe"

"Get me a trade signal for BTC on Binance, 1h timeframe"

BTC Signal Result

That's it. Your Claude now has a quant analyst built in.


Tools

get_trade_signal

Returns a composite BUY / SELL / HOLD verdict with confidence score for any supported asset on any of 5 supported exchanges — crypto perps, TradFi perpetuals (stocks, indices, commodities, FX), and liquidity-filtered meme coins on Hyperliquid.

Under the hood: a multi-factor scoring engine evaluates momentum, trend structure, derivatives sentiment, open interest dynamics, and volume conviction. Scores pass through regime-aware filters and adaptive post-processing gates — including funding flow analysis, volatility regime detection, and trend persistence decay — before a final verdict is emitted.

Only high-conviction calls are generated. The engine is designed to stay silent when the edge is unclear.

Parameters:

  • coin (string, required): Asset symbol — e.g. "ETH", "BTC", "SOL", "GOLD", "TSLA", or any of 290+ supported assets
  • timeframe (string, default "15m"): "1m", "3m", "5m", "15m", "30m", "1h", "2h", "4h", "8h", "12h", "1d"
  • exchange (string, default "HL"): "HL" (Hyperliquid), "BINANCE", "BYBIT", "OKX", "BITGET". TradFi assets (GOLD, TSLA, etc.) are HL-only.
  • includeReasoning (boolean, default true): Human-readable explanation of the call logic

Output includes: call direction, confidence score (0–100), all computed indicator values, detected market regime, reasoning narrative, and _algovault metadata for downstream tool composability.

scan_funding_arb

Scans cross-venue funding rate differentials across Hyperliquid, Binance, and Bybit. Normalizes hourly vs 8-hour rate conventions, computes basis-point spreads, and ranks opportunities by composite score (spread magnitude, time urgency, and funding conviction from 24h history). OKX and Bitget funding data is available via their respective adapters — arb scanning expansion is planned.

This is the only MCP server that provides cross-venue funding arbitrage intelligence — long one exchange, short another, capture the spread.

Parameters:

  • minSpreadBps (number, default 5): Minimum spread in basis points to include
  • limit (number, default 10): Maximum results returned

Output includes: per-opportunity venue rates, optimal long/short direction, annualized spread percentage, and next funding timestamps.

get_market_regime

Classifies the current market environment into one of four regimes: TRENDING_UP, TRENDING_DOWN, RANGING, or VOLATILE.

Uses a multi-dimensional classification approach combining directional strength measurement with ADX slope analysis (detecting trend strengthening vs exhaustion), volume-weighted pivot detection, ATR-adaptive funding thresholds, and cross-venue funding sentiment divergence. The regime classification directly informs how get_trade_signal filters its output — agents can also use it independently for strategy selection and position sizing.

Parameters:

  • coin (string, required): Asset symbol
  • timeframe (string, default "4h"): Candle timeframe for analysis
  • exchange (string, default "HL"): Exchange to analyze — same options as get_trade_signal

Output includes: regime label, confidence score, underlying metrics (trend strength, volatility interpretation, price structure), cross-venue funding sentiment, and a plain-English strategy suggestion.


Performance Tracking

Every call is tracked from emission to outcome. No exceptions.

What we measure:

  • Outcome prices at timeframe-appropriate evaluation windows
  • PFE Win Rate — did price move in the call direction at any point during the evaluation window
  • Expected Value — probability-weighted average return per call
  • Profit Factor — gross wins divided by gross losses
  • Peak Favorable Excursion (PFE) and Maximum Adverse Excursion (MAE)
  • Running statistics per asset, timeframe, and quality tier

HOLD calls are free — when the engine says "don't trade," you don't pay. Only BUY and SELL verdicts are charged via x402 or count against subscription quotas. This aligns our incentives: you only pay when we see a tradeable opportunity.

  • HOLD Rate: Percentage of scans where the engine declines to issue a trade call. A high HOLD rate (currently ~84%) means the engine is selective — it only calls BUY/SELL when conditions align across multiple indicators.

Infrastructure:

  • Remote mode: PostgreSQL with automated outcome backfill
  • Local mode: SQLite at ~/.crypto-quant-signal/performance.db
  • Only high-confidence BUY/SELL calls are tracked — HOLD is excluded
  • Signals are tracked per exchange — the track record shows performance on each venue independently

On-Chain Verification

Every call is hashed (keccak256) at creation time and anchored on Base L2 via daily Merkle batches. This makes the track record tamper-proof — we cannot edit past calls.

  • Contract: 0x6485...0f81 (Base L2)
  • Verify any call: https://api.algovault.com/api/verify-signal?signalId=<ID>
  • View all batches: https://api.algovault.com/api/merkle-batches
  • Visual verification: algovault.com/verify

Pricing

Feature Free Starter ($9.99/mo) Pro ($49/mo) Enterprise ($299/mo) x402 (per call)
Exchanges HL only All 5 All 5 All 5 All 5
Assets BTC, ETH All 290+ All 290+ All 290+ All 290+
Asset classes Crypto only Crypto + TradFi Crypto + TradFi Crypto + TradFi Crypto + TradFi
Timeframes 15m, 1h All 11 All 11 All 11 All 11
Funding arb results Top 5 Unlimited Unlimited Unlimited Unlimited
Track record Full access Full access Full access Full access Full access
Monthly calls ~100/day 3,000/mo 15,000/mo 100,000/mo Unlimited
Support Community Email Priority Dedicated
Price $0 $9.99/mo $49/mo $299/mo $0.01–0.05/call
HOLD calls Free Free Free Free Free

* HOLD verdicts (engine says "don't trade") are always free across all tiers — no x402 charge, no quota deduction.

x402 micropayments: AI agents pay per HTTP call with USDC on Base — no signup, no API key, no billing. The payment receipt is the credential. See x402.org.

Subscriptions: Sign up at api.algovault.com/signup. Starter ($9.99/mo) unlocks all assets and timeframes. API key delivered instantly after checkout.


For Developers

Remote endpoint (recommended)

https://api.algovault.com/mcp

Streamable HTTP transport. Compatible with any MCP client — Claude, Cursor, Cline, custom agents.

Local install via npx

npx -y crypto-quant-signal-mcp

Claude Desktop / Cursor config

{
  "mcpServers": {
    "crypto-quant-signal": {
      "command": "npx",
      "args": ["-y", "crypto-quant-signal-mcp"],
      "env": { "TRANSPORT": "stdio" }
    }
  }
}

npm install

npm install crypto-quant-signal-mcp

Self-hosting

git clone https://github.com/AlgoVaultLabs/crypto-quant-signal-mcp
cd crypto-quant-signal-mcp
cp .env.example .env  # Edit with your values
npm ci && npm run build
docker compose up -d

Architecture

Agent / Claude / Cursor
  │
  ▼
api.algovault.com/mcp (Streamable HTTP)
  │
  ├─ x402 payment verification (USDC on Base)
  ├─ API key / subscription check
  ├─ Free tier fallback
  │
  ▼
MCP Server (Express + @modelcontextprotocol/sdk)
  │
  ├─ Composite Scoring Engine
  │    ├─ Multi-factor indicator fusion
  │    ├─ Regime-aware signal filtering
  │    └─ Adaptive post-processing gates
  │
  ├─ Asset Classification Engine
  │    ├─ 4-tier quality system (Blue Chip → Major Alt → TradFi → Meme)
  │    └─ Liquidity filter for meme/micro assets
  │
  ├─ Exchange Adapter Layer
  │    ├─ Hyperliquid (crypto + TradFi xyz perps)
  │    ├─ Binance USDT-M Futures
  │    ├─ Bybit Linear
  │    ├─ OKX Swap
  │    └─ Bitget USDT-M
  │
  ├─ Performance Tracker
  │    └─ PostgreSQL (remote) / SQLite (local)
  │
  └─ Exchange Public APIs (free, no auth — all 5 venues)

Exchange adapter pattern: All exchange interactions go through the ExchangeAdapter interface — supporting full signal generation on all 5 exchanges. Each adapter implements candles, OI, funding rates, and current price via native exchange APIs. TradFi perps are Hyperliquid-exclusive.


Suite Composability

Every tool output includes an _algovault metadata block declaring version and compatible downstream tools:

This tool Feeds into (Phase 2+)
get_trade_signal crypto-quant-risk-mcp (position sizing) · crypto-quant-backtest-mcp (validation)
scan_funding_arb crypto-quant-execution-mcp (optimal entry/exit) · crypto-quant-risk-mcp (exposure)
get_market_regime crypto-quant-risk-mcp (regime-aware sizing) · crypto-quant-backtest-mcp (filtered backtests)

Schemas are designed for composability. All tools share consistent timestamp, coin, and _algovault fields — downstream tools accept these objects directly as input.


Privacy

Local mode: Zero telemetry. No data sent to AlgoVault servers. Call history stored on your machine only.

Remote mode: Request metadata logged for analytics (IP hashed, never stored raw). See privacy policy.


License

MIT


Disclaimer: AlgoVault provides directional entry interpretation for AI agents. Exit timing is determined by your agent or strategy. This is not financial advice. Past performance does not guarantee future results.

Built by AlgoVault Labs

Landing page · API endpoint

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选