About AI Trading Agent
AI Trading Agent is an MCP server in the Finance category: build your own AI hedge fund with Claude, Codex, Cursor & OpenClaw. The agent-native skills directory for Trader Dev MCP — write Pine Script, backtest crypto strategies, optimize parameters. It has been installed 0 times through Conduid.
Install
git clone https://github.com/flukelaster/ai-trading-agentThis server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.
Ask AI
Ask AI about AI Trading Agent
Powered by Claude · Grounded in docs
Security checks
- ·README presentNot checked yet.
- ·License declaredNot checked yet.
- ·Tests presentNot checked yet.
- ·Dependencies pinnedNot checked yet.
- ·No dynamic code executionNot checked yet.
- ·Scoped permissionsNot checked yet.
README
AI Trading Agent
Multi-symbol autonomous trading platform powered by Claude AI agents
Trades GOLD · OILCash · BTCUSD · USDJPY through MetaTrader 5
Features · Screenshots · Architecture · Quick Start · Pages
✨ Highlights
Eight specialist Claude agents collaborating on a virtual trading floor — Orchestrator, Technical, Fundamental, Risk, Reflector, Sentiment, Strategy Optimizer, and Single-Agent fallback. Hard guardrails prevent runaway trades. Real-time UI streams every decision, position, and P&L tick.
📑 Table of Contents
- Features
- Screenshots
- Architecture
- Tech Stack
- Pages Overview
- Quick Start
- Project Structure
- Environment Variables
🚀 Features
| Domain | Capability |
|---|---|
| 🧠 Multi-Agent AI | 8 specialist Claude agents (Sonnet + Haiku) — Orchestrator + Technical + Fundamental + Risk + Reflector + Sentiment + Optimizer |
| 🛡️ Guardrails | Non-bypassable limits at MCP tool layer (lot size, daily loss, trade frequency, cooldowns) |
| 🎯 Strategy Engine | 5 strategies + ensemble (EMA, RSI, Breakout, Mean Reversion, ML Signal) with regime-adaptive switching |
| 🤖 ML Models | Per-symbol LightGBM with 40+ features, drift detection, auto-retrain, calibration analysis |
| 📊 Real-time Dashboard | Live ticks, positions, P&L, equity chart, AI insights, multi-symbol tabs |
| 🪙 Token Cost Tracking | Per-agent token + cost monitoring with daily breakdown and 90-day retention |
| 🔐 Secrets Vault | AES-256-GCM encrypted credential storage, OAuth token health monitor |
| 📰 News & Sentiment | RSS + macro feeds, Claude sentiment analyzer with bullish/bearish/neutral scoring |
| ⚖️ Quantitative Analysis | VaR, Sharpe, Sortino, drawdown, Monte Carlo, walk-forward, cointegration |
| 🚦 Gradual Rollout | Shadow → Paper → Micro-Live → Live deployment modes |
| 🔁 Self-Reflection | Reflector agent reviews past trades and writes lessons to session memory |
| 📡 Live WebSocket | Real-time price, position, sentiment, and bot event streaming |
| 🔑 Passkey Auth | WebAuthn-ready (currently JWT/password active on Railway) |
| 📨 Telegram Alerts | Trade open/close, signal, AI analysis, system health (Thai language) |
📸 Screenshots
Drop PNGs into
docs/screenshots/with the filenames below.
🏠 Dashboard — Live Trading View
📈 Backtest Studio
📜 Trade History & Performance
🧠 AI Insights
⚡ AI Activity Timeline
💰 AI Usage & Cost Monitor
🤖 ML Model Monitoring
🌐 Macro Data
🛡️ Quant Risk Dashboard
🏢 AI Trading Floor — Agent Prompts
🔌 Integration Status
🔔 Notifications Center
⚙️ Settings
🏗 Architecture
┌──────────────────────────────────────────────────────────────────────┐
│ Frontend (Next.js 16, Vercel/Railway) │
│ Dashboard · Backtest · History · AI Insights · AI Usage · ML │
└──────────────────────┬───────────────────────────────────────────────┘
│ HTTPS + WebSocket
▼
┌──────────────────────────────────────────────────────────────────────┐
│ Backend (FastAPI, Railway) │
│ ├── Auth Layer (JWT cookie · Passkey WebAuthn ready) │
│ ├── Secrets Vault (AES-256-GCM · HKDF key derivation) │
│ ├── Runner Manager (process / Docker sandbox) │
│ │ ├── Job Queue (Redis + DB-persisted) │
│ │ ├── Heartbeat Monitor (auto-restart) │
│ │ └── Agent Entrypoint (asyncio loop) │
│ │ ├── MCP Tool Server (14 modules · 40+ tools) │
│ │ ├── Guardrails (non-bypassable trading limits) │
│ │ └── Multi-Agent Pipeline │
│ │ ├── Reflector (Haiku) — past trade review │
│ │ ├── Technical Analyst (Haiku) — indicators │
│ │ ├── Fundamental Analyst (Haiku) — sentiment │
│ │ ├── Risk Analyst (Haiku) — portfolio risk │
│ │ ├── Sentiment Analyzer (Haiku) — news scoring │
│ │ ├── Strategy Optimizer (Haiku) — param tuning │
│ │ └── Orchestrator (Sonnet) — final decision │
│ ├── Strategy Engine (5 strategies + ensemble + MTF + regime) │
│ ├── ML Models (LightGBM per-symbol · drift detection) │
│ ├── AI Usage Logger (token + cost per call · 90d retention) │
│ ├── PostgreSQL 15 + Redis 7 (AOF persistence) │
│ └─── HTTP ────► Windows VPS │
│ └── MT5 Bridge + MetaTrader 5 (XM Global) │
└──────────────────────────────────────────────────────────────────────┘
🛠 Tech Stack
| Layer | Technology |
|---|---|
| Backend | FastAPI 0.115 · SQLAlchemy 2.0 (async) · asyncpg · APScheduler |
| Frontend | Next.js 16 · React 19 · Tailwind 4 · Zustand · lightweight-charts · recharts |
| AI | Claude Code SDK (Max subscription) + Anthropic SDK fallback · Sonnet 4 + Haiku 4.5 |
| ML | LightGBM · scikit-learn · pandas · 40+ features per symbol |
| Auth | JWT Bearer (active) · WebAuthn Passkey (ready) |
| Trading | MetaTrader 5 via custom HTTP Bridge (Windows VPS) |
| CI/CD | GitHub Actions (ruff · pytest · tsc · build) · Railway auto-deploy |
| DB | PostgreSQL 15 (14 Alembic migrations) · Redis 7 (AOF) |
| Notifications | Telegram bot (trade signals · AI analysis · system alerts) |
| Testing | pytest (444 tests · 27 files) · SQLite in-memory · fakeredis · MT5 mock |
📄 Pages Overview
| Route | Page | Purpose |
|---|---|---|
/dashboard |
Trading Dashboard | Live ticks, positions, P&L, equity chart, AI insights, multi-symbol tabs |
/backtest |
Backtest Studio | Run backtests, optimizer, walk-forward, Monte Carlo, overfitting score |
/history |
Trade History | Past trades + performance breakdown (P&L, equity curve, archive demo) |
/insights |
AI Insights | News sentiment + Claude optimization reports |
/activity |
AI Activity | Unified timeline of agent decisions, sentiment runs, errors |
/ai-usage |
AI Usage | Per-agent token consumption + equivalent USD cost (90-day window) |
/ml |
ML Model | LightGBM training, drift detection, calibration, predictions |
/macro |
Macro Data | FRED indicators, economic calendar, correlations |
/quant |
Quant Risk | VaR, regime, correlation matrix, volatility, portfolio, stress test |
/agent-prompts |
Trading Floor | Customize per-agent system prompts (chibi character avatars) |
/integration |
Integration | Service connectivity status (DB, Redis, MT5, Vault, OAuth) |
/notifications |
Notifications | Event history with filters |
/settings |
Settings | Per-symbol risk, AI filter toggle, paper trade switch |
/login |
Login | Passkey or password authentication |
/setup |
Setup | First-time passkey registration wizard |
⚡ Quick Start
Prerequisites
- Python 3.12+
- Node.js 22+
- Docker (for local PostgreSQL + Redis)
- Windows VPS with MetaTrader 5 (production trading only)
1. Start databases
docker-compose up -d
2. Backend
cd backend
python -m venv .venv
source .venv/bin/activate # Windows: .venv\Scripts\activate
pip install -r requirements.txt
cp .env.example .env
alembic upgrade head
uvicorn app.main:app --reload --port 8000
3. MT5 Bridge (Windows VPS only)
cd mt5_bridge
pip install -r requirements.txt
cp .env.example .env # add MT5 credentials
uvicorn main:app --host 0.0.0.0 --port 8001
4. Frontend
cd frontend
npm install
cp .env.example .env.local
npm run dev
5. Run tests
cd backend
python -m pytest tests/ -v --no-cov # 444 tests
📁 Project Structure
gold-trading-bot/
├── backend/
│ ├── app/
│ │ ├── api/routes/ # 80+ REST endpoints
│ │ ├── ai/ # Claude client, pricing, usage logger
│ │ ├── bot/ # Trading engine, scheduler, health monitor
│ │ ├── strategy/ # 5 strategies + ensemble + regime
│ │ ├── risk/ # Risk manager, circuit breaker, correlation
│ │ ├── ml/ # LightGBM trainer, features, drift
│ │ ├── runner/ # Docker sandbox runner system
│ │ ├── db/ # SQLAlchemy models + 15 migrations
│ │ └── ...
│ ├── alembic/versions/ # DB migrations
│ ├── mcp_server/
│ │ ├── server.py # FastMCP tool server
│ │ ├── guardrails.py # Non-bypassable trading limits
│ │ ├── agents/ # 6 specialist agents + orchestrator
│ │ └── tools/ # 14 tool modules
│ └── tests/ # 444 tests (27 files)
├── frontend/
│ ├── app/ # Next.js App Router (15 pages, no runners)
│ ├── components/ # UI primitives + layout
│ ├── lib/ # API client + WebSocket
│ └── public/agent-characters/ # Chibi agent portraits
├── mt5_bridge/ # MetaTrader 5 HTTP bridge (Windows VPS)
├── agent-character/ # Source character art (PNG)
├── docs/
│ ├── logo/ # Logo assets
│ └── screenshots/ # README screenshots
├── scripts/backup_db.sh # Daily pg_dump
└── docker-compose.yml
🔧 Environment Variables
See backend/.env.example and mt5_bridge/.env.example.
| Variable | Purpose |
|---|---|
DATABASE_URL / DATABASE_URL_SYNC |
PostgreSQL connection (asyncpg + sync for Alembic) |
REDIS_URL |
Redis connection |
SECRET_KEY |
JWT signing key |
VAULT_MASTER_KEY |
AES-256-GCM root key for Secrets Vault |
CLAUDE_CODE_OAUTH_TOKEN |
Claude Max subscription token |
MT5_BRIDGE_URL / MT5_BRIDGE_API_KEY |
Windows VPS bridge endpoint |
AGENT_MODE |
single (Phase C) or multi (Phase D) |
ROLLOUT_MODE |
shadow · paper · micro · live |
MAX_RISK_PER_TRADE / MAX_DAILY_LOSS / MAX_LOT |
Hard risk limits |
TELEGRAM_BOT_TOKEN / TELEGRAM_CHAT_ID |
Telegram alerts |
📜 License
Private — internal use only.
Built with Claude Code · Deployed on Railway · Trading on MT5
README mirrored from the source repository 20 days ago. The original is authoritative.