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MCP server · Finance

AI Trading Agent

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.

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Scored 20 days ago · breakdown

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.

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Clone
git clone https://github.com/flukelaster/ai-trading-agent

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README

AI Trading Agent

Multi-symbol autonomous trading platform powered by Claude AI agents

Trades GOLD · OILCash · BTCUSD · USDJPY through MetaTrader 5

Python FastAPI Next.js PostgreSQL Redis Claude Railway License

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

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.

Questions

About AI Trading Agent

How do I install AI Trading Agent?

Run git clone https://github.com/flukelaster/ai-trading-agent, then add the server to your MCP client's configuration. Conduid has recorded 0 installs, so the command is known to work with current clients.

Is AI Trading Agent safe to use with an AI agent?

Its trust score is 39 out of 100 (low). Conduid hasn't run static security checks on this repository yet, so review the source yourself before granting it credentials. It has no ConduID identity yet, so agent calls to it are not receipted.

Is AI Trading Agent still maintained?

Conduid hasn't recorded a commit date for this repository yet. Check the repository directly for recent activity.