Crypto Indicators MCP Server
An MCP server providing a range of cryptocurrency technical analysis indicators and strategies, empowering AI trading agents to efficiently analyze market trends and develop robust quantitative strategies.
Features
- Technical Indicators : 50+ indicators across trend, momentum, volatility, and volume categories.
- Trading Strategies : Corresponding strategies outputting signals:
-1 (SELL), 0 (HOLD), 1 (BUY).
- Flexible Data Source : Defaults to Binance, configurable to any
ccxt-supported exchange.
- Modular Design : Indicators and strategies are categorized for easy maintenance.
Installation
Prerequisites
- Node.js (v18.x or higher)
- npm (v8.x or higher)
Steps
Clone the Repository :
git clone https://github.com/kukapay/crypto-indicators-mcp.git
cd crypto-indicators-mcp
Install Dependencies :
npm install
Configure MCP Client : To use this server with an MCP client like Claude Desktop, add the following to your config file (or equivalent):
{
"mcpServers": {
"crypto-indicators-mcp": {
"command": "node",
"args": ["path/to/crypto-indicators-mcp/index.js"],
"env": {
"EXCHANGE_NAME": "binance"
}
}
}
}
Available Tools
Trend Indicators
calculate_absolute_price_oscillator: Measures the difference between two EMAs to identify trend strength (APO).calculate_aroon: Identifies trend changes and strength using high/low price extremes (Aroon).calculate_balance_of_power: Gauges buying vs. selling pressure based on price movement (BOP).calculate_chande_forecast_oscillator: Predicts future price movements relative to past trends (CFO).calculate_commodity_channel_index: Detects overbought/oversold conditions and trend reversals (CCI).calculate_double_exponential_moving_average: Smooths price data with reduced lag for trend detection (DEMA).calculate_exponential_moving_average: Weights recent prices more heavily for trend analysis (EMA).calculate_mass_index: Identifies potential reversals by measuring range expansion (MI).calculate_moving_average_convergence_divergence: Tracks momentum and trend direction via EMA differences (MACD).calculate_moving_max: Computes the maximum price over a rolling period (MMAX).calculate_moving_min: Computes the minimum price over a rolling period (MMIN).calculate_moving_sum: Calculates the sum of prices over a rolling period (MSUM).calculate_parabolic_sar: Provides stop-and-reverse points for trend following (PSAR).calculate_qstick: Measures buying/selling pressure based on open-close differences (Qstick).calculate_kdj: Combines stochastic and momentum signals for trend analysis (KDJ).calculate_rolling_moving_average: Applies a rolling EMA for smoother trend tracking (RMA).calculate_simple_moving_average: Averages prices over a period to identify trends (SMA).calculate_since_change: Tracks the time since the last significant price change.calculate_triple_exponential_moving_average: Reduces lag further than DEMA for trend clarity (TEMA).calculate_triangular_moving_average: Weights middle prices more for smoother trends (TRIMA).calculate_triple_exponential_average: Measures momentum with triple smoothing (TRIX).calculate_typical_price: Averages high, low, and close prices for a balanced trend view.calculate_volume_weighted_moving_average: Incorporates volume into moving averages for trend strength (VWMA).calculate_vortex: Identifies trend direction and strength using true range (Vortex).
Momentum Indicators
calculate_awesome_oscillator: Measures market momentum using midline crossovers (AO).calculate_chaikin_oscillator: Tracks accumulation/distribution momentum (CMO).calculate_ichimoku_cloud: Provides a comprehensive view of support, resistance, and momentum (Ichimoku).calculate_percentage_price_oscillator: Normalizes MACD as a percentage for momentum (PPO).calculate_percentage_volume_oscillator: Measures volume momentum via EMA differences (PVO).calculate_price_rate_of_change: Tracks price momentum as a percentage change (ROC).calculate_relative_strength_index: Identifies overbought/oversold conditions via momentum (RSI).calculate_stochastic_oscillator: Compares closing prices to ranges for momentum signals (STOCH).calculate_williams_r: Measures momentum relative to recent high-low ranges (Williams %R).
Volatility Indicators
calculate_acceleration_bands: Frames price action with dynamic volatility bands (AB).calculate_average_true_range: Measures market volatility based on price ranges (ATR).calculate_bollinger_bands: Encloses price action with volatility-based bands (BB).calculate_bollinger_bands_width: Quantifies volatility via band width changes (BBW).calculate_chandelier_exit: Sets trailing stop-losses based on volatility (CE).calculate_donchian_channel: Tracks volatility with high/low price channels (DC).calculate_keltner_channel: Combines ATR and EMA for volatility bands (KC).calculate_moving_standard_deviation: Measures price deviation for volatility (MSTD).calculate_projection_oscillator: Assesses volatility relative to projected prices (PO).calculate_true_range: Calculates daily price range for volatility analysis (TR).calculate_ulcer_index: Quantifies downside volatility and drawdowns (UI).
Volume Indicators
calculate_accumulation_distribution: Tracks volume flow to confirm price trends (AD).calculate_chaikin_money_flow: Measures buying/selling pressure with volume (CMF).calculate_ease_of_movement: Assesses how easily prices move with volume (EMV).calculate_force_index: Combines price and volume for momentum strength (FI).calculate_money_flow_index: Identifies overbought/oversold via price-volume (MFI).calculate_negative_volume_index: Tracks price changes on lower volume days (NVI).calculate_on_balance_volume: Accumulates volume to predict price movements (OBV).calculate_volume_price_trend: Combines volume and price for trend confirmation (VPT).calculate_volume_weighted_average_price: Averages prices weighted by volume (VWAP).
Trend Strategies
calculate_absolute_price_oscillator_strategy: Generates buy/sell signals from APO crossovers (APO Strategy).calculate_aroon_strategy: Signals trend reversals using Aroon crossovers (Aroon Strategy).calculate_balance_of_power_strategy: Issues signals based on BOP thresholds (BOP Strategy).calculate_chande_forecast_oscillator_strategy: Predicts reversals with CFO signals (CFO Strategy).calculate_kdj_strategy: Combines KDJ lines for trend-based signals (KDJ Strategy).calculate_macd_strategy: Uses MACD crossovers for trading signals (MACD Strategy).calculate_parabolic_sar_strategy: Signals trend direction with PSAR shifts (PSAR Strategy).calculate_typical_price_strategy: Generates signals from typical price trends.calculate_volume_weighted_moving_average_strategy: Issues signals based on VWMA crossovers (VWMA Strategy).calculate_vortex_strategy: Signals trend direction with Vortex crossovers (Vortex Strategy).
Momentum Strategies
calculate_momentum_strategy: Issues signals based on momentum direction.calculate_awesome_oscillator_strategy: Signals momentum shifts with AO crossovers (AO Strategy).calculate_ichimoku_cloud_strategy: Generates signals from Ichimoku cloud positions (Ichimoku Strategy).calculate_rsi2_strategy: Signals overbought/oversold with RSI thresholds (RSI Strategy).calculate_stochastic_oscillator_strategy: Uses stochastic crossovers for signals (STOCH Strategy).calculate_williams_r_strategy: Signals momentum reversals with Williams %R (Williams %R Strategy).
Volatility Strategies
calculate_acceleration_bands_strategy: Signals breakouts with acceleration bands (AB Strategy).calculate_bollinger_bands_strategy: Issues signals from Bollinger Band breaches (BB Strategy).calculate_projection_oscillator_strategy: Signals volatility shifts with PO (PO Strategy).
Volume Strategies
calculate_chaikin_money_flow_strategy: Signals volume pressure with CMF (CMF Strategy).calculate_ease_of_movement_strategy: Issues signals based on EMV trends (EMV Strategy).calculate_force_index_strategy: Signals momentum with force index shifts (FI Strategy).calculate_money_flow_index_strategy: Signals overbought/oversold with MFI (MFI Strategy).calculate_negative_volume_index_strategy: Signals trends with NVI changes (NVI Strategy).calculate_volume_weighted_average_price_strategy: Issues signals from VWAP crossovers (VWAP Strategy).
Usage Examples
Example 1: Calculate MACD Indicator
Input (Natural Language Prompt) :
Calculate the MACD for BTC/USDT on a 1-hour timeframe with fast period 12, slow period 26, signal period 9, and fetch 100 data points.
Output :
{"macd": [...], "signal": [...], "histogram": [...]}
Example 2: Calculate RSI Strategy
Input (Natural Language Prompt) :
Give me the RSI strategy signals for ETH/USDT on a 4-hour timeframe with a period of 14 and 50 data points.
Output :
[-1, 0, 1, 0, ...]
License
This project is licensed under the MIT License - see the LICENSE file for details.
