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Roadmap & Status

A consolidated view of what has been built, what is planned next, and what lies further ahead.

Overview

Phase Status Key Deliverables
Phase 1 -- Strategy Platform :white_check_mark: Complete MCP server (78 tools), strategy layer, dashboard, Docker deployment, 63 tests
Phase 2 -- Supporting MCPs :material-clock-outline: Planned Data Feed MCP, Broker Session MCP, Trade Execution MCP
Phase 3 -- Decision Engine :material-clock-outline: Planned Automated evaluation, backtesting, trade journaling
Phase 4 -- Knowledge System :material-calendar-blank-outline: Future Outcome logging, parameter tuning, anomaly detection

Phase 1 -- Strategy Platform :white_check_mark:

Status: Complete

The foundation of the ICT Edge Fund platform is fully operational.

  • tradingview-mcp -- 78 MCP tools for controlling and reading from TradingView Desktop via the Chrome DevTools Protocol.
  • tradingview-strategy -- ICT strategy layer with readers, interpreters, and a signal engine that processes indicator output into actionable trade signals.
  • Dashboard -- Live web dashboard serving signals, chart screenshots, and indicator settings on port 8000.
  • Docker deployment -- Production-ready docker-compose.yml with nginx reverse proxy, SSL via certbot, and MkDocs documentation site.
  • Test suite -- 63 unit tests covering all interpreters and the strategy engine, using the Node.js built-in test runner.
  • Domains -- ictedgefund.com (dashboard) and docs.ictedgefund.com (this wiki) are live.

Phase 2 -- Supporting MCPs

Status: Planned

Three new MCP servers that extend the platform beyond chart reading into data, brokerage, and execution.

Data Feed MCP

  • Historical OHLCV data beyond the visible chart range
  • Tick-level data for precise entry/exit analysis
  • Economic calendar integration (FOMC, NFP, CPI, etc.)
  • Session schedule awareness (London, New York, Asia open/close times)

Broker Session MCP

  • NinjaTrader and Interactive Brokers authentication
  • Account state queries (balance, margin, buying power)
  • Position and order inventory
  • Margin requirement checks before order submission

Trade Execution MCP

  • Full order lifecycle: place, modify, cancel
  • Risk enforcement layer (max position size, daily loss limits)
  • Human confirmation gate -- no order is sent without explicit approval
  • Order status tracking and fill notifications

Phase 3 -- Decision Engine

Status: Planned

Bringing automation closer to the decision process while keeping a human in the loop.

  • Automated strategy evaluation -- The engine analyzes signals and proposes trades, but every action requires human confirmation before execution.
  • Backtesting framework -- Replay mode that runs historical data through the strategy layer to measure performance without live risk.
  • Performance tracking and trade journaling -- Automatic logging of every trade with entry/exit rationale, screenshots, and P&L attribution.

Phase 4 -- Knowledge System

Status: Future

Long-term intelligence layer that learns from historical outcomes.

  • Outcome logging -- Every signal and trade outcome is recorded for pattern analysis.
  • Parameter tuning -- Adjust indicator and strategy parameters based on historical win rates and risk-adjusted returns.
  • Anomaly detection -- Flag unusual market conditions or strategy behavior that deviates from historical norms.