MCP Trading Agent v3.0 — ICT / SMC + News Sentiment

======================================================

A production-ready MCP server exposing 13 market-data, news,

backtesting, and persistence tools to an LLM agent (Nexus v2).

The agent learns from backtests and applies those rules to

live analysis — compounding its edge over time.

Quick Start

-----------

1. Install dependencies:

pip install -r requirements.txt

2. Run the server (stdio transport for Claude Desktop / Claude Code):

python server.py

3. Or run with HTTP transport (for MCP Inspector / web):

set MCP_TRANSPORT=streamable-http

python server.py

4. Test with the MCP Inspector:

npx -y @modelcontextprotocol/inspector

# Then connect to http://localhost:8000/mcp

Claude Desktop Integration

--------------------------

Add this to your Claude Desktop config (~/.claude/config.json):

{

"mcpServers": {

"trading-agent": {

"command": "python",

"args": ["C:\Github\ai-company\mcp-trading-agent\server.py"]

}

}

}

Project Structure

-----------------

mcp-trading-agent/

├── server.py # 13 MCP tool registrations + entry point

├── config.py # ServerConfig dataclass (v2.0.0)

├── system_prompt.py # Nexus v2 persona — 7 command workflows

├── CLAUDE.md # Auto-loaded by Claude Code (same as above)

├── requirements.txt # mcp[cli], yfinance, ddgs, pandas, numpy

├── README.md # This file

├── v2_upgrade_walkthrough.md # Architecture & evolution docs

├── tools/

│ ├── market_data.py # 7 functions: OHLC, liquidity, backtest,

│ │ # intraday backtest, MTF fetch, breakout scan

│ ├── news.py # fetch_market_news (DuckDuckGo / ddgs)

│ ├── risk_reward.py # get_risk_to_reward_setup

│ └── persistence.py # HTML reports, lessons.md CRUD,

│ # sync_trading_knowledge (SHA-256 dedup)

└── data/ # Persistent state (auto-created on first run)

├── lessons.md # Knowledge base — rules learned from backtests

├── lessons.hashes # SHA-256 fingerprints for dedup sidecar

└── reports/ # HTML analysis reports (30-day auto-purge)

All 13 MCP Tools

----------------

v1 — Original (5 tools)

┌──────────────────────────────┬──────────────────────────────────────────┐

│ Tool │ Purpose │

├──────────────────────────────┼──────────────────────────────────────────┤

│ get_daily_ohlc │ Daily OHLCV candles (60-day default) │

│ get_intraday_ohlc │ Sub-daily candles (1m/5m/15m/30m/60m) │

│ identify_liquidity_pools │ Swing high/low detection (BSL / SSL) │

│ fetch_market_news │ DuckDuckGo news search (fundamental bias)│

│ get_risk_to_reward_setup │ RR ratio + quality verdict │

└──────────────────────────────┴──────────────────────────────────────────┘

v2 — Stateful / Backtest (6 tools)

┌──────────────────────────────┬──────────────────────────────────────────┐

│ Tool │ Purpose │

├──────────────────────────────┼──────────────────────────────────────────┤

│ get_historical_backtest_data │ Extended OHLCV w/ swing flags (10-500d) │

│ run_intraday_backtest │ Auto SMC scan: sweep+FVG, RR>=3, w-fwd │

│ manage_html_report │ Save HTML + auto-open browser + 30d purge│

│ read_lessons_learned │ Read lessons.md knowledge base │

│ update_lessons_learned │ Append free-form insights to lessons.md │

│ sync_trading_knowledge │ SHA-256 dedup + persist structured rules │

└──────────────────────────────┴──────────────────────────────────────────┘

v3 — Breakout Scanner (2 tools)

┌──────────────────────────────┬──────────────────────────────────────────┐

│ Tool │ Purpose │

├──────────────────────────────┼──────────────────────────────────────────┤

│ get_multi_timeframe_data │ Monthly + Weekly + Daily OHLC in one call│

│ scan_for_breakout │ 1-10 score across M/W/D timeframes │

└──────────────────────────────┴──────────────────────────────────────────┘

Agent Commands (plain-text, not slash commands)

-----------------------------------------------

Command Data Source

──────────────────────────────────────────────────────────────────

backtest [ticker] [days] get_historical_backtest_data

backtest intraday [ticker] [days] [intv] run_intraday_backtest

analyze [ticker] get_daily_ohlc + liquidity

entry [ticker] (runs analyze silently first)

intraday [ticker] get_intraday_ohlc — 1:3 RR gate

view [ticker] get_daily_ohlc — macro swing

breakout [ticker or list] get_multi_timeframe_data +

scan_for_breakout

Example session:

backtest intraday NIFTY 60 15m

→ automated SMC scan, equity curve HTML, rules saved to lessons.md

intraday NIFTY

→ live 15m analysis with 1:3 RR gate, HTML report auto-opened

breakout NIFTY, BTC, GOLD

→ D/W/M alignment matrix, conviction scores, trigger prices

analyze AAPL

→ fundamental + technical confluence, HTML report

entry AAPL

→ tight trade card: entry / SL / target / RR / verdict

Breakout Scoring (scan_for_breakout)

-------------------------------------

Scoring breakdown (10 pts max):

Monthly (3 pts): price > EMA-6, near BSL <= 5%, 2/3 months bullish

Weekly (3 pts): price > EMA-20, volatility contraction, near BSL <= 3%

Daily (4 pts): price > EMA-20, displacement candle, FVG present,

volume spike >= 1.3× 20-day avg

Conviction tiers:

8-10 HIGH (high_conviction_confirmed when M + W both BULLISH)

5-7 MODERATE (Watch and Wait)

1-4 LOW (no confluence)

Trigger price = nearest daily BSL above current price.

Supported Ticker Aliases

------------------------

NIFTY → ^NSEI, BANKNIFTY → ^NSEBANK, SENSEX → ^BSESN,

SPX → ^GSPC, SPY → SPY, QQQ → QQQ, DXY → DX-Y.NYB,

GOLD → GC=F, CRUDE → CL=F, BTC → BTC-USD, ETH → ETH-USD

Intraday Backtest — What run_intraday_backtest Returns

-------------------------------------------------------

Per-trade fields:

setup_type, direction, sweep_time, session_label, hour,

swept_level, fvg_zone, entry, stop_loss, target,

risk_pts, reward_pts, rr, atr_at_setup, is_consecutive_sweep,

outcome (WIN/LOSS/OPEN), exit_price

Aggregate stats:

win_rate_pct, avg_rr, profit_factor, max_drawdown_r,

expectancy_r, equity_curve (R-multiple list), session_breakdown

session_breakdown keys (Opening/Morning/Midday/Afternoon/Closing):

total, wins, losses, open_trades, win_rate_pct

Knowledge Persistence

---------------------

lessons.md is automatically maintained across sessions.

sync_trading_knowledge uses SHA-256 fingerprints stored in

lessons.hashes to prevent near-duplicate rules accumulating.

HTML reports older than 30 days are auto-purged by manage_html_report.

License: MIT