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CryptoSignal-MCP

๐Ÿ“ˆ CryptoSignal MCP

Python MCP License Binance

AI-Powered Cryptocurrency Direction Prediction & Market Signal Analysis

Powered by Machine Learning Ensemble Models with 30+ Technical Indicators

Features โ€ข Installation โ€ข API Tools โ€ข Examples โ€ข Indicators

๐ŸŽฌ Demo


โœจ Features

Feature

Description

๐Ÿง 

Advanced ML Predictions

Ensemble models (Random Forest + Gradient Boosting) with 30+ technical indicators

๐Ÿ“Š

Comprehensive Technical Analysis

RSI, MACD, Bollinger Bands, Stochastic, Williams %R, ATR, and more

โฐ

Multiple Timeframes

Support for 1m, 3m, 5m, 15m, 30m, 1h, 2h, 4h, 6h, 8h, 12h, 1d, 3d, 1w, 1M

๐Ÿ”„

Real-time Data

Live market data from Binance API with intelligent rate limiting and caching

๐ŸŽฏ

Smart Filtering

Automatically filters incomplete trading periods for accurate analysis

๐Ÿ”

WebSearch Integration

Optimized search queries for Claude Code's WebSearch tool with sentiment analysis prompts

๐Ÿ“Š

Polymarket Trader Analysis

Monitor successful crypto traders' activities, positions, and trading patterns for behavioral insights

๐Ÿš€ Installation

Prerequisites

  • Python 3.11+

  • Required packages (automatically installed)

Quick Start

# Clone the repository git clone https://github.com/khalilbalaree/CryptoSignal-MCP.git cd CryptoSignal-MCP # Install dependencies pip install -r requirements.txt # Run the server python crypto_predictor_server.py

๐Ÿ”ง MCP Integration

With Claude Desktop

Add this server to your Claude Desktop configuration:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%/Claude/claude_desktop_config.json

{ "mcpServers": { "cryptosignal-mcp": { "command": "python", "args": ["/path/to/CryptoSignal-MCP/crypto_predictor_server.py"], "env": {} } } }

๐Ÿ› ๏ธ API Tools

๐ŸŽฏ predict_crypto_direction

Advanced ML prediction using ensemble models to predict price direction

predict_crypto_direction( symbol="BTCUSDT", # Trading pair interval="1h", # Time interval (default: 1h) training_periods=1000 # Training data size (default: 1000) )

Supported Intervals: 1m 3m 5m 15m 30m 1h 2h 4h 6h 8h 12h 1d 3d 1w 1M

Returns: Prediction direction, confidence scores, model performance, market context, feature importance, risk assessment


๐Ÿ“ˆ analyze_crypto_indicators

Fast technical analysis without ML training - immediate market insights

analyze_crypto_indicators( symbol="ETHUSDT", # Trading pair interval="1h", # Time interval (default: 1h) limit=100, # Data points (default: 100) short_period=5, # Short-term period (default: 5) medium_period=10, # Medium-term period (default: 10) long_period=20 # Long-term period (default: 20) )

Returns: Moving averages, trends, momentum analysis, volatility metrics, support/resistance levels, trend signals


๐Ÿ” get_crypto_news_search

Generate optimized search queries for Claude Code's WebSearch tool

get_crypto_news_search( symbol="bitcoin" # Crypto symbol (default: bitcoin) )

Returns: Structured search data including optimized queries, reliable domains, and analysis prompts for use with Claude Code's WebSearch tool


๐Ÿ“Š monitor_polymarket_trader

Analyze successful crypto traders' positions and patterns on Polymarket

monitor_polymarket_trader( trader_address="0x1234567890abcdef1234567890abcdef12345678", # Ethereum wallet address limit=100 # Activities to fetch (default: 100) )

Returns: Complete trading activity history including positions, bet sizes, outcomes, timing, and P&L performance across crypto prediction markets

๐Ÿ’ก Usage Examples

# Get ML prediction for Bitcoin (1-hour timeframe) predict_crypto_direction("BTCUSDT", "1h", 1000) # Quick technical analysis for Ethereum (4-hour timeframe) analyze_crypto_indicators("ETHUSDT", "4h", 200) # Get search query for Bitcoin news analysis get_crypto_news_search("bitcoin") # Monitor successful crypto trader's activities monitor_polymarket_trader("0x1234567890abcdef1234567890abcdef12345678", 100)
# Short-term scalping prediction (15-minute intervals) predict_crypto_direction("BTCUSDT", "15m", 500) # Long-term investment analysis (daily timeframe) analyze_crypto_indicators("ETHUSDT", "1d", 365, 10, 20, 50) # Custom altcoin analysis analyze_crypto_indicators("ADAUSDT", "2h", 100, 3, 7, 14) # Multi-timeframe analysis for timeframe in ["1h", "4h", "1d"]: analyze_crypto_indicators("BTCUSDT", timeframe) # Copy trading successful traders successful_traders = [ "0x1234567890abcdef1234567890abcdef12345678", "0xabcdef1234567890abcdef1234567890abcdef12" ] for trader in successful_traders: monitor_polymarket_trader(trader, 100)

๐Ÿ“Š Technical Indicators

Our ML models leverage 30+ advanced technical indicators across multiple categories:

Category

Indicators

๐Ÿ“ˆ Price & Momentum

Price change, acceleration, velocity

Momentum (3, 5, 10, 20 periods)

Rate of change, Sharpe ratio

๐Ÿ“‰ Moving Averages

Simple MA (5, 10, 20, 50)

Exponential MA (5, 12, 26, 50)

MA ratios and crossover signals

๐ŸŽฏ Oscillators

RSI (7, 14 periods)

Stochastic Oscillator (K%, D%)

Williams %R

๐Ÿ”Š Volume Analysis

Volume ratios and rate of change

On-Balance Volume (OBV)

Volume spikes and trends

๐Ÿ“ Volatility & Bands

Bollinger Bands (width, position)

Average True Range (ATR)

Volatility regimes

๐Ÿ—๏ธ Market Structure

Support/resistance levels

Fractal patterns (local max/min)

Trend strength and regime detection

๐ŸŽฏ Model Architecture

graph TD A[Historical Data] --> B[Feature Engineering] B --> C[30+ Technical Indicators] C --> D[Data Preprocessing] D --> E[Ensemble Models] E --> F[Random Forest] E --> G[Gradient Boosting] E --> H[Extra Trees] F --> I[Voting Classifier] G --> I H --> I I --> J[Prediction + Confidence]

โš ๏ธ Risk Disclaimer

๐Ÿšจ IMPORTANT: This tool is designed for educational and research purposes only.

Cryptocurrency trading involves significant financial risk. Past performance does not guarantee future results. Always:

  • Conduct your own research and analysis

  • Implement proper risk management strategies

  • Never invest more than you can afford to lose

  • Consider seeking advice from qualified financial professionals

๐Ÿ“„ License

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


Built with โค๏ธ for the crypto community

โญ Star this repo โ€ข ๐Ÿ› Report Issues โ€ข ๐Ÿ’ก Request Features

-
security - not tested
A
license - permissive license
-
quality - not tested

remote-capable server

The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.

AI-Powered Cryptocurrency Direction Prediction & Market Signal Analysis

  1. ๐ŸŽฌ Demo
    1. โœจ Features
      1. ๐Ÿš€ Installation
        1. Prerequisites
        2. Quick Start
        3. ๐Ÿ”ง MCP Integration
      2. ๐Ÿ› ๏ธ API Tools
        1. ๐ŸŽฏ predict_crypto_direction
        2. ๐Ÿ“ˆ analyze_crypto_indicators
        3. ๐Ÿ” get_crypto_news_search
        4. ๐Ÿ“Š monitor_polymarket_trader
      3. ๐Ÿ’ก Usage Examples
        1. ๐Ÿ“Š Technical Indicators
          1. ๐ŸŽฏ Model Architecture
            1. โš ๏ธ Risk Disclaimer
              1. ๐Ÿ“„ License

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