TradePilot MCP Server
A production-grade MCP server that integrates Polygon.io market data with an 18-layer technical analysis engine to generate actionable options trading signals and high-probability playbooks.
README
🚀 TradePilot MCP Server v3.0
Advanced 18-Layer Trading Intelligence Engine
A production-grade MCP (Model Context Protocol) server that combines Polygon.io real-time market data with an 18-layer technical analysis engine for autonomous options trading intelligence.
📊 What is This?
TradePilot is a FastAPI-based MCP server that:
- Fetches real-time and historical market data from Polygon.io
- Runs analysis through 18 specialized layers (Technical + Price Action + Options + Master Brain)
- Provides 14 high-probability playbooks targeting 85-95% win rates
- Delivers actionable options trading signals with precise strike/expiry recommendations
- Includes multi-ticker scanning, risk management, and alert notifications
Think of it as your AI options trading copilot powered by institutional-grade analysis.
🎯 Key Features
-
18-Layer Analysis System
- Layers 1-10: Technical indicators (Momentum, Volume, Trend, Structure)
- Layers 11-13: Price action (Support/Resistance, VWAP, Volume Profile)
- Layers 14-17: Options analysis (IV, Greeks, Gamma, Put/Call ratios)
- Layer 18: Master Brain with 14 playbooks
-
Trading Modes
- SCALP: 0-2 DTE options
- SWING: 7-45 DTE options
- INTRADAY: Same-day trades
-
Advanced Features
- Multi-ticker scanner with filtering
- Kelly Criterion position sizing
- Risk management with drawdown protection
- Discord/Slack/Telegram alerts
- Backtesting engine
- AI-ready JSON output
🚀 Quick Start
# Clone the repository
git clone https://github.com/Sakhir786/tradepilot-mcp-server.git
cd tradepilot-mcp-server
# Set up environment
python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt
# Configure environment variables
cp .env.example .env
# Edit .env and add your POLYGON_API_KEY
# Run the server
python main.py
# Or with uvicorn:
uvicorn main:app --host 0.0.0.0 --port 10000
Access documentation at: http://localhost:10000/docs
📡 API Endpoints
18-Layer Analysis
GET /engine18/analyze- Full 18-layer analysisGET /engine18/quick- Quick signal checkGET /engine18/scan- Multi-ticker scannerGET /engine18/playbooks- List all 14 playbooksGET /engine18/health- System health check
Market Data (Polygon.io)
GET /candles- OHLCV dataGET /options- Options chainGET /news- Latest newsGET /ticker-details- Company info
🔧 Environment Variables
POLYGON_API_KEY=your_api_key_here
TRADEPILOT_PRODUCTION_PATH=/path/to/tradepilot-mcp-server
TRADEPILOT_LAYERS_PATH=/path/to/layers
TRADEPILOT_PORTFOLIO_VALUE=100000
TRADEPILOT_DISCORD_WEBHOOK=your_webhook_url
📊 Example Usage
import requests
# Full analysis
response = requests.get(
"http://localhost:10000/engine18/analyze",
params={"symbol": "SPY", "mode": "swing"}
)
analysis = response.json()
print(f"Direction: {analysis['analysis_summary']['direction']}")
print(f"Win Probability: {analysis['analysis_summary']['win_probability']}%")
🎯 14 High-Probability Playbooks
Bullish (CALLS):
- Liquidity Sweep + BOS (85-95%)
- CHoCH Reversal (82-92%)
- Trend Continuation (80-90%)
- FVG Fill + Rejection (81-88%)
- Order Block Bounce (79-87%)
- Divergence + Structure (80-88%)
- VWAP Reclaim (77-85%)
Bearish (PUTS): 8-14. Mirror patterns for bearish setups
🔐 Security & Best Practices
- Never commit
.envfiles - Keep API keys secure
- Use environment variables for sensitive data
- Enable rate limiting for production deployments
📝 License
MIT License - See LICENSE file for details
🤝 Contributing
Contributions welcome! Please open an issue or submit a pull request.
📧 Support
For issues or questions, please open a GitHub issue.
TradePilot v3.0 - Professional Options Trading Intelligence 🚀📈
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.