Crypto Indicators MCP Server provides AI trading agents with access to over 50 technical analysis indicators and trading strategies for cryptocurrency markets. Built on the Model Context Protocol, it fetches real-time OHLCV data from Binance (configurable to any CCXT-supported exchange) and calculates trend, momentum, volatility, and volume indicators. Each tool returns either raw indicator values or actionable trading signals (-1 for sell, 0 for hold, 1 for buy), enabling AI agents to analyze market conditions and develop quantitative trading strategies without implementing complex technical analysis algorithms themselves.
Measures the difference between two EMAs to identify trend strength (APO).
Identifies trend changes and strength using high/low price extremes (Aroon).
Gauges buying vs. selling pressure based on price movement (BOP).
Predicts future price movements relative to past trends (CFO).
Detects overbought/oversold conditions and trend reversals (CCI).
Smooths price data with reduced lag for trend detection (DEMA).
Weights recent prices more heavily for trend analysis (EMA).
Identifies potential reversals by measuring range expansion (MI).
Tracks momentum and trend direction via EMA differences (MACD).
Computes the maximum price over a rolling period (MMAX).
Computes the minimum price over a rolling period (MMIN).
Calculates the sum of prices over a rolling period (MSUM).
Provides stop-and-reverse points for trend following (PSAR).
Measures buying/selling pressure based on open-close differences (Qstick).
Combines stochastic and momentum signals for trend analysis (KDJ).
Applies a rolling EMA for smoother trend tracking (RMA).
Averages prices over a period to identify trends (SMA).
Tracks the time since the last significant price change.
Reduces lag further than DEMA for trend clarity (TEMA).
Weights middle prices more for smoother trends (TRIMA).
Measures momentum with triple smoothing (TRIX).
Averages high, low, and close prices for a balanced trend view.
Incorporates volume into moving averages for trend strength (VWMA).
Identifies trend direction and strength using true range (Vortex).
Measures market momentum using midline crossovers (AO).
Tracks accumulation/distribution momentum (CMO).
Provides a comprehensive view of support, resistance, and momentum (Ichimoku).
Normalizes MACD as a percentage for momentum (PPO).
Measures volume momentum via EMA differences (PVO).
Tracks price momentum as a percentage change (ROC).
Identifies overbought/oversold conditions via momentum (RSI).
Compares closing prices to ranges for momentum signals (STOCH).
Measures momentum relative to recent high-low ranges (Williams %R).
Frames price action with dynamic volatility bands (AB).
Measures market volatility based on price ranges (ATR).
Encloses price action with volatility-based bands (BB).
Quantifies volatility via band width changes (BBW).
Sets trailing stop-losses based on volatility (CE).
Tracks volatility with high/low price channels (DC).
Combines ATR and EMA for volatility bands (KC).
Measures price deviation for volatility (MSTD).
Assesses volatility relative to projected prices (PO).
Calculates daily price range for volatility analysis (TR).
Quantifies downside volatility and drawdowns (UI).
Tracks volume flow to confirm price trends (AD).
Measures buying/selling pressure with volume (CMF).
Assesses how easily prices move with volume (EMV).
Combines price and volume for momentum strength (FI).
Identifies overbought/oversold via price-volume (MFI).
Tracks price changes on lower volume days (NVI).
Accumulates volume to predict price movements (OBV).
Combines volume and price for trend confirmation (VPT).
Averages prices weighted by volume (VWAP).
Generates buy/sell signals from APO crossovers (APO Strategy).
Signals trend reversals using Aroon crossovers (Aroon Strategy).
Issues signals based on BOP thresholds (BOP Strategy).
Predicts reversals with CFO signals (CFO Strategy).
Combines KDJ lines for trend-based signals (KDJ Strategy).
Uses MACD crossovers for trading signals (MACD Strategy).
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