crypto-indicators-mcp

What is crypto-indicators-mcp?

crypto-indicators-mcp is an MCP (Multi-Chain Protocol) server designed to provide a comprehensive suite of cryptocurrency technical analysis indicators and trading strategies. It empowers AI trading agents to analyze market trends efficiently and develop robust quantitative strategies.

How to use crypto-indicators-mcp?

To use crypto-indicators-mcp, you need Node.js (v18.x or higher) and npm (v8.x or higher).

1. Clone the Repository:

   git clone https://github.com/kukapay/crypto-indicators-mcp.git
   cd crypto-indicators-mcp
   

2. Install Dependencies:

   npm install
   

3. Configure MCP Client: Add the following to your MCP client's config file (e.g., Claude Desktop):

    {
      "mcpServers": {
        "crypto-indicators-mcp": {
          "command": "node",
          "args": ["path/to/crypto-indicators-mcp/index.js"],
          "env": {
            "EXCHANGE_NAME": "binance"
          }
        }
      }
    }   
   

Once configured, you can interact with the server using natural language prompts to calculate indicators or get strategy signals. For example:

• Calculate MACD Indicator: "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."
• Calculate RSI Strategy: "Give me the RSI strategy signals for ETH/USDT on a 4-hour timeframe with a period of 14 and 50 data points."

Key Features of crypto-indicators-mcp

• Technical Indicators: Offers over 50 indicators covering trend, momentum, volatility, and volume categories.
• Trading Strategies: Provides corresponding strategies that output trading signals: -1 (SELL), 0 (HOLD), 1 (BUY).
• Flexible Data Source: Defaults to Binance but can be configured to work with any ccxt-supported exchange.
• Modular Design: Indicators and strategies are well-categorized for easy maintenance and extensibility.

Use Cases of crypto-indicators-mcp

• AI Trading Agents: Empowers AI trading agents with robust technical analysis capabilities for automated trading.
• Quantitative Strategy Development: Facilitates the development and testing of quantitative trading strategies.
• Market Trend Analysis: Provides tools for in-depth analysis of cryptocurrency market trends.
• Custom Trading Bots: Can be integrated into custom trading bots to enhance their decision-making processes.

FAQ from crypto-indicators-mcp

Q: What are the prerequisites for running crypto-indicators-mcp? A: You need Node.js (v18.x or higher) and npm (v8.x or higher).

Q: Which cryptocurrency exchanges are supported? A: It defaults to Binance, but it can be configured to work with any exchange supported by ccxt.

Q: What kind of signals do the trading strategies output? A: The strategies output -1 for SELL, 0 for HOLD, and 1 for BUY signals.

Q: Is there a license for this project? A: Yes, this project is licensed under the MIT License.

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

1. Clone the Repository:

   git clone https://github.com/kukapay/crypto-indicators-mcp.git
   cd crypto-indicators-mcp
   

2. Install Dependencies:

   npm install
   

3. 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.