⚠️ Research and education only. AI Trader MCP does not place real trades, send real orders, or guarantee profits. Backtests are not future performance. Crypto trading is risky and leverage can cause catastrophic losses. Read docs/DISCLAIMER.md before doing anything.
“Just like human traders have TradingView, AI agents need their own quant research desk.”
Most AI tools help traders write code. AI Trader MCP helps AI agents run the entire research workflow — generate hypotheses, write Pine Script, backtest, optimize, compare, and report. Built by DaviddTech, backtesting live on YouTube for 5+ years.
⚡ 30-second quickstart
🤖 Prefer to hand it all to your AI? Open WORKBOOK.md and paste it into any MCP-capable agent. It’s a step-by-step, self-contained install and usage guide written for AI agents to follow top to bottom.
1. Install Trader Dev MCP in your agent (pick one):
# Claude Code
claude mcp add --transport sse --scope user trader-dev https://mcp.trader.dev/sse
# Codex
codex mcp add trader-dev -- npx -y mcp-remote https://mcp.trader.dev/sse
# Cursor / OpenClaw / Cline / Continue / Windsurf / Gemini CLI
Register https://mcp.trader.dev/sse as a remote SSE MCP server.
2. Paste this one-liner to your agent:
Read https://raw.githubusercontent.com/DaviddTech/ai-trading-agent/main/SKILL.md
and help me build an AI hedge fund research desk using Trader Dev MCP.
3. Ship your first backtest:
Backtest a Bollinger Band squeeze breakout on the top 10 Bybit pairs at 1h.
Report profit factor, max drawdown, and stability across symbols.
Reject overfit results.
That’s it. Your agent is now a quant.
🔥 Why AI Trader MCP
| Without AI Trader MCP |
With AI Trader MCP |
| Open TradingView, hand-code Pine Script, click backtest, copy results into a spreadsheet. |
“Backtest this strategy on the top 10 Bybit pairs at 1h.” Done in one message. |
| Click-optimize parameters one input at a time. |
Parameter sweeps across stop loss, take profit, ATR multiples, regime filters — natural language. |
| Forget which version of a strategy worked last week. |
Strategies live in Trader Dev. Fork, version, compare, promote, demote — all from chat. |
| Pay for a quant team. |
Spin up a Mathematician, Mean-Reversion Engineer, Strategy Optimizer, and Position Optimizer — for free. |
| Wonder if your backtest is curve-fit. |
Built-in robustness discipline: multi-pair, multi-timeframe, drawdown control, honest verdict labels. |
| Use AI to write code. |
Use AI to run the whole research desk. |
🏭 Don’t want to build your own strategies?
Not every trader wants to be a quant researcher. If you’d rather skip the research and run trading bots that already work, StrategyFactory.ai is where they live.
- 400+ trading bots — every one backtested and forward-tested with real-money live results
- No Pine Script knowledge required — pick a bot, plug in, go
- Real performance data — not curve-fit screenshots, not “based on backtest” — actual live results
- Plays nicely with this repo — the AI Trader MCP skills can analyze, fork, and improve any Strategy Factory bot
| Path |
What you do |
Where to start |
| 🛠 Build it yourself |
Use the skills, prompts, and loop roles in this repo. Pine Script + backtests + optimization, all from chat. |
Stay here |
| 🚀 Use what already works |
Browse the marketplace, pick a bot, plug into your trading stack. |
strategyfactory.ai |
→ Browse 400+ live-tested trading bots at StrategyFactory.ai →
🧠 The skills directory
Each skill is a focused, agent-readable SKILL.md that turns your AI client into a specialist on the desk.
| Skill |
What it does |
| Main SKILL.md |
The entrypoint. Routes your agent into the right workflow. Start here. |
| AI Hedge Fund Manager |
Coordinates the research desk. Picks specialists. Enforces discipline. |
| Quant Mathematician |
Renaissance-style first-principles strategy creation. No retail indicator soup. |
| Mean Reversion Engineer |
Engineered mean-reversion systems for crypto. Volatility-aware, regime-filtered. |
| Strategy Optimizer |
Searches Trader Dev for existing strategies. Forks. Improves. Compares against baseline. |
| Position Optimizer |
Tests leverage, fractional Kelly, vol-targeting, drawdown throttling, bounded recovery. Keeps entries frozen. |
Plus copy-paste workflow prompts in prompts/ and examples/.
🔁 The 24/7 desk — loop roles
One conversation. Fifteen specialists. Forever. Every role is TradingView-native — pure Pine Script and OHLCV, no off-chain data feeds.
Drop any of these into your AI client’s /loop command and walk away. Each role fires every 15 minutes, runs one focused research cycle through Trader Dev MCP, and writes a structured report.
# Greenfield strategy creation, every 15 minutes
/loop 15m read loop/01-quant-mathematician.md and execute it
# Risk audits the existing book, every 15 minutes
/loop 15m read loop/08-risk-manager.md and execute it
Full guide: loop/README.md.
📈 What you can build
- An AI hedge fund research desk — generate hypotheses → Pine Script → backtest → compare → report.
- A Pine Script generator — paste a strategy idea, get clean, no-repaint, no-lookahead Pine.
- A TradingView backtest worker — paste any Pine script, get a multi-pair, multi-timeframe robustness report.
- A parameter optimizer — sweep stops, TPs, ATR multiples, filters; reject overfits.
- A position-sizing lab — improve P&L by tuning leverage/Kelly/vol-targeting without changing entries.
- A live signal monitor — pipe Trader Dev signals to Telegram alerts.
- A strategy fork-and-improve loop — search the strategy library, fork winners, iterate one variable at a time.
🤖 Works with
If your agent speaks MCP, AI Trader MCP works.
💬 Example session
You: I want to test a volatility breakout idea on crypto.
Use the Quant Mathematician skill.
Agent: Hypothesis: when realized volatility compresses below the
20-period historical median for 8+ bars, a breakout in
either direction has positive expectancy on 1h crypto.
[writes Pine Script — no repaint, no lookahead]
[calls mcp__trader-dev__run_backtest across 10 pairs × 4 timeframes]
Results:
Net profit: +38.4%
Profit factor: 1.62
Max drawdown: -14.1%
Trades: 412
Stable on 7/10 pairs across 1h, 2h, 4h.
Fails on BTC and ETH — needs trend filter.
Verdict: Incubate.
Next iteration: add ADX < 25 regime filter.
(Illustrative format. Numbers depend on your strategy, market, and assumptions.)
🛠 Powered by Trader Dev MCP
Trader Dev is the live MCP server doing the heavy lifting. Agents connected to it can:
- 🔍
search_strategies — discover proven strategy ideas
- ⚙️
create_strategy / update_strategy / fork_strategy — version your research
- 📊
run_backtest / quick_backtest — backtest Pine Script across crypto pairs
- 🎯
optimize_strategy — automated parameter sweeps
- 🔬
compare_backtests — diff versions side by side
- 📈
get_equity_curve / get_trades / get_backtest_result — pull granular metrics
- 📡
get_recent_signals / list_active_alerts / test_telegram_sink — live signal monitoring
- 💼
promote_strategy / demote_strategy — lifecycle management
Full tool reference: docs/AGENT_GUIDE.md. Agents should always call tools/list first — never guess arguments.
🪙 Current market support
Trader Dev currently works on crypto pairs.
If we get enough interest, we’ll add US stocks, Forex, and Futures next.
🗺 Roadmap
Live now
- Trader Dev MCP server (SSE)
- Pine Script backtesting from any MCP-compatible agent
- Crypto pair coverage
- Parameter and position optimization workflows
- 5 specialist agent skills + prompt library
- Telegram alert workflows
In progress
- Native AI Trader alert system (less reliance on TradingView alerts)
- Backtest screenshots and shareable report cards pulled from the web app
- Downloadable Pine Scripts from the web app
- Risk Manager, PineScript Developer, Backtest Analyst, and Report Writer skills
- Walk-forward and Monte Carlo robustness checks
Community-requested
- Forex, stocks, futures
- More exchange data sources
- Strategy tournament leaderboards
- AI quant team presets by trading style
🧪 Research standards
This is not a hype trading bot. The skills are written to enforce:
- ✅ Robustness across symbols and nearby timeframes
- ✅ Drawdown control and profit factor over raw net profit
- ✅ Honest verdict labels — Reject / Watchlist / Incubate / Candidate / Production candidate
- ✅ No repainting, no lookahead, no future data
- ❌ No martingale without strict caps
- ❌ No one-coin cherry-picked backtests
- ❌ No hidden liquidation risk
⭐ Star history
If this repo saves you a single evening of manual backtesting, give it a star.
🤝 Contributing
Great contributions:
- New prompts and agent skills
- Pine Script strategy templates
- Backtest report formats
- Risk-management workflows
- Translations
- Demo videos and screenshots
See CONTRIBUTING.md. Open an issue with Skill request or share a result with Backtest result.
- 🐦 Twitter / X — follow @DaviddTech for new strategies and AI quant updates
- 🎥 YouTube — 5 years of live strategy backtesting on DaviddTech
- 🌐 Website — davidd.tech
- 💬 Discord — coming soon — watch the repo to be notified
❓ FAQ
Is this a trading bot?
No. It is a skills directory that lets AI agents talk to the Trader Dev MCP server. Trader Dev runs the backtests; the skills tell your agent how to behave like a quant researcher.
Does it place real trades?
No. AI Trader MCP is for research, backtesting, and education. Live signals can be piped to Telegram, but execution is your responsibility.
Which AI agents are supported?
Anything that speaks MCP — Claude Code, Codex, Cursor, OpenClaw, Cline, Continue, Windsurf, Gemini CLI, and any custom agent using the Model Context Protocol.
Why Pine Script?
Because TradingView is where most traders already live, and Pine Script is the fastest path from idea to backtest. Python/Polars support is on the roadmap.
How is this different from virattt/ai-hedge-fund?
That repo is a Python simulation of named-investor personas. AI Trader MCP is the infrastructure layer — an MCP server plus skills that any AI agent can use to actually generate, backtest, and optimize Pine Script strategies. They are complementary.
Do I need a Trader Dev account?
Some MCP tools require authentication. See docs/QUICKSTART.md.
Will this make me money?
No promises, no guarantees, no financial advice. See the disclaimer.
🛡 Risk notice
Trading is risky. Crypto is risky. Leverage is risky. Backtests are not guarantees. This project is for research, backtesting, and education only. Always paper trade and forward test before considering any live deployment. The authors and contributors accept no responsibility for losses. Full text: docs/DISCLAIMER.md.
📄 License
MIT — see LICENSE.
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