MindLayer TradingView MCP Agent

MindLayer TradingView MCP Agent

A powerful integration system that connects TradingView's Pine Script indicators with MindLayer's MCP (Model Context Protocol) for advanced cryptocurrency trading signals based on RSI and Stochastic RSI.

Overview

This system consists of three main components:

1. Pine Script Indicator: A TradingView indicator that analyzes RSI and Stochastic RSI to generate buy/sell signals.
2. MCP Agent: A Python application that processes these signals and communicates with MCP-enabled systems.
3. REST API: An HTTP API that allows programmatic access to all MCP agent functionality.

Features

• 📊 RSI & Stochastic RSI Analysis: Generates signals based on these powerful momentum indicators
• 🔄 Multi-Timeframe Analysis: Confirms signals using higher timeframe data
• 📱 Real-time Alerts: Sends alerts via TradingView's webhook system
• 🤖 MCP Integration: Seamlessly integrates with MindLayer's Model Context Protocol
• 📈 Adaptive Confidence Levels: Each signal includes a strength indicator (1-5)
• 🛡️ Risk Management: Configurable risk profiles based on your trading style
• 🌐 RESTful API: Access all functionality programmatically via HTTP API

Setup Instructions

TradingView Indicator Setup

1. Log in to your TradingView account
2. Go to Pine Editor
3. Create a new indicator and paste the contents of MindLayer_MCP_Signal.pine
4. Save and add to chart
5. Configure the indicator settings according to your preferences

System Setup

1. Clone this repository
2. Install required dependencies:
   pip install -r requirements.txt
3. Configure your settings (edit config.py or use environment variables)
4. Start the system using the launcher script:
   # Run just the MCP agent python run.py agent # Run just the API server (which includes the agent) python run.py api # Run both the agent and API server separately (advanced) python run.py both

Command Line Options

The run.py script accepts several command-line arguments:

TradingView Alert Setup

1. Open your chart with the MindLayer MCP Signal indicator
2. Right-click on the indicator and select "Add Alert"
3. Set condition to trigger on "MindLayer MCP Buy Signal" or "MindLayer MCP Sell Signal"
4. In the webhook URL field, enter your MCP agent's webhook URL (e.g., http://your-server:8000) or the API webhook endpoint (e.g., http://your-server:5000/api/webhook)
5. In the message field, paste the following JSON template:
   { "ticker": "{{ticker}}", "type": "{{strategy.order.action}}", "confidence": {{plot("Buy Signal")}} or {{plot("Sell Signal")}}, "price": {{close}}, "rsi": {{rsi}}, "stoch": {{stoch}}, "htf_rsi": {{plot("HTF RSI")}}, "htf_stoch": {{plot("HTF Stoch")}} }
6. Save the alert

Configuration

Environment Variables

You can configure the system using environment variables (create a .env file):

Pine Script Customization

The TradingView indicator is highly customizable:

• Risk Profile: Conservative, Moderate, or Aggressive
• RSI Parameters: Change length and overbought/oversold thresholds
• Stochastic RSI Parameters: Adjust K, D periods and thresholds
• Visual Settings: Customize colors and display options

Signal Interpretation

Buy Signals

• Strong Buy: Green arrow with high confidence rating (4-5)
• Moderate Buy: Light green arrow with medium confidence rating (2-3)
• Weak Buy: Dotted green arrow with low confidence rating (1)

Sell Signals

• Strong Sell: Red arrow with high confidence rating (4-5)
• Moderate Sell: Light red arrow with medium confidence rating (2-3)
• Weak Sell: Dotted red arrow with low confidence rating (1)

How It Works

1. The Pine Script indicator analyzes price action using RSI and Stochastic RSI
2. When conditions meet your configured criteria, it displays a buy/sell signal on the chart
3. TradingView sends an alert via webhook to your MCP agent or API
4. The MCP agent processes the signal and communicates with MCP-enabled systems
5. (Optional) The agent can execute trades based on these signals

REST API Documentation

The system includes a comprehensive REST API for programmatic access to all functionality.

API Endpoints

Signal Management

• GET /api/signals - Get all trading signals
• GET /api/signals?symbol=BTCUSDT - Get signals for a specific symbol
• POST /api/signals - Manually create a new signal

Indicator Values

• GET /api/indicators - Get all indicator values
• GET /api/indicators?symbol=BTCUSDT - Get indicator values for a specific symbol

Agent Control

• GET /api/status - Get current agent status
• POST /api/start - Start the MCP agent
• POST /api/stop - Stop the MCP agent

Configuration

• GET /api/config - Get current configuration
• PUT /api/config - Update configuration settings

Webhook

• POST /api/webhook - Receive webhook from TradingView

API Documentation

• GET /api/docs - Get detailed API documentation

API Usage Examples

Get Current Agent Status

Get All Signals

Create a Manual Signal

Update Configuration

Requirements

• Python 3.7+
• TradingView account (Pro plan recommended for webhook alerts)
• Server or cloud instance to run the MCP agent and API (if using webhooks)

System Architecture

Best Practices

• Always test thoroughly in a paper trading environment before using real funds
• Combine these signals with other analysis and risk management techniques
• Higher timeframe signals tend to be more reliable than very short timeframes
• Consider market conditions that might impact signal reliability
• Secure your API server behind proper authentication if exposing to the internet

Support

If you encounter issues or have questions, please open an issue on this repository.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Disclaimer

Trading cryptocurrency involves substantial risk. Past performance of this indicator does not guarantee future results. Always use proper risk management and never trade with funds you cannot afford to lose.