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An MCP server providing a range of cryptocurrency technical analysis indicators and strategies.
Configuration
View docs{
"mcpServers": {
"kukapay-crypto-indicators-mcp": {
"command": "node",
"args": [
"path/to/crypto-indicators-mcp/index.js"
],
"env": {
"EXCHANGE_NAME": "binance"
}
}
}
}You can run the Crypto Indicators MCP Server to access a wide range of cryptocurrency technical indicators and trading signals. It enables AI trading agents to analyze market trends, apply dozens of indicators, and generate buy/sell/hold decisions across multiple timeframes and data sources.
To use this MCP server with an MCP client, run the local server process and point your client at the configured MCP entry. The server exposes numerous indicators and corresponding strategies that output signals like -1 (SELL), 0 (HOLD), and 1 (BUY). You can configure the data source to your preferred exchange (default is Binance) and select the indicators or strategies you want for your trading workflow.
Prerequisites: Node.js v18.x or higher and npm v8.x or higher.
Step 1: Clone the repository and navigate into the project folder.
git clone https://github.com/kukapay/crypto-indicators-mcp.git
cd crypto-indicators-mcpStep 2: Install dependencies.
npm installStep 3: Configure the MCP client to connect to this server. Use the following MCP config snippet to run the server locally via Node.
{
"mcpServers": {
"crypto-indicators-mcp": {
"command": "node",
"args": ["path/to/crypto-indicators-mcp/index.js"],
"env": {
"EXCHANGE_NAME": "binance"
}
}
}
}The server defaults to Binance for market data but can be configured to any exchange supported by CCXT. Use the ENV var EXCHANGE_NAME to switch the data source when running the MCP client configuration.
If you encounter connection issues, verify that the Node process starts correctly and that the MCP client config points to the correct index.js path and exchange name. Ensure you have network access to the chosen exchange's data endpoints.
This project is licensed under the MIT License. Use it in compliance with the license terms and attribute appropriately where required.
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).
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).
Signals trend direction with PSAR shifts (PSAR Strategy).
Generates signals from typical price trends.
Issues signals based on VWMA crossovers (VWMA Strategy).
Signals trend direction with Vortex crossovers (Vortex Strategy).
Issues signals based on momentum direction.
Signals momentum shifts with AO crossovers (AO Strategy).
Generates signals from Ichimoku cloud positions (Ichimoku Strategy).
Signals overbought/oversold with RSI thresholds (RSI Strategy).
Uses stochastic crossovers for signals (STOCH Strategy).
Signals momentum reversals with Williams %R (Williams %R Strategy).
Signals breakouts with acceleration bands (AB Strategy).
Issues signals from Bollinger Band breaches (BB Strategy).
Signals volatility shifts with PO (PO Strategy).
Signals volume pressure with CMF (CMF Strategy).
Issues signals based on EMV trends (EMV Strategy).
Signals momentum with force index shifts (FI Strategy).
Signals overbought/oversold with MFI (MFI Strategy).
Signals trends with NVI changes (NVI Strategy).
Issues signals from VWAP crossovers (VWAP Strategy).