coin_analysis
Analyze cryptocurrency performance using technical indicators and metrics for specific coins, exchanges, and timeframes to support trading decisions.
Instructions
Get detailed analysis for a specific coin on specified exchange and timeframe.
Args:
symbol: Coin symbol (e.g., "ACEUSDT", "BTCUSDT")
exchange: Exchange name (BINANCE, KUCOIN, etc.)
timeframe: Time interval (5m, 15m, 1h, 4h, 1D, 1W, 1M)
Returns:
Detailed coin analysis with all indicators and metricsInput Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| symbol | Yes | ||
| exchange | No | KUCOIN | |
| timeframe | No | 15m |
Implementation Reference
- src/tradingview_mcp/server.py:361-496 (handler)The coin_analysis tool handler. Uses tradingview_ta.get_multiple_analysis to fetch indicators for the specified symbol, computes metrics using compute_metrics, and returns a comprehensive analysis dictionary including price data, Bollinger Band analysis, technical indicators (RSI, MACD, ADX, Stoch), and market sentiment.
@mcp.tool() def coin_analysis( symbol: str, exchange: str = "KUCOIN", timeframe: str = "15m" ) -> dict: """Get detailed analysis for a specific coin on specified exchange and timeframe. Args: symbol: Coin symbol (e.g., "ACEUSDT", "BTCUSDT") exchange: Exchange name (BINANCE, KUCOIN, etc.) timeframe: Time interval (5m, 15m, 1h, 4h, 1D, 1W, 1M) Returns: Detailed coin analysis with all indicators and metrics """ try: exchange = sanitize_exchange(exchange, "KUCOIN") timeframe = sanitize_timeframe(timeframe, "15m") # Format symbol with exchange prefix if ":" not in symbol: full_symbol = f"{exchange.upper()}:{symbol.upper()}" else: full_symbol = symbol.upper() screener = EXCHANGE_SCREENER.get(exchange, "crypto") try: analysis = get_multiple_analysis( screener=screener, interval=timeframe, symbols=[full_symbol] ) if full_symbol not in analysis or analysis[full_symbol] is None: return { "error": f"No data found for {symbol} on {exchange}", "symbol": symbol, "exchange": exchange, "timeframe": timeframe } data = analysis[full_symbol] indicators = data.indicators # Calculate all metrics metrics = compute_metrics(indicators) if not metrics: return { "error": f"Could not compute metrics for {symbol}", "symbol": symbol, "exchange": exchange, "timeframe": timeframe } # Additional technical indicators macd = indicators.get("MACD.macd", 0) macd_signal = indicators.get("MACD.signal", 0) adx = indicators.get("ADX", 0) stoch_k = indicators.get("Stoch.K", 0) stoch_d = indicators.get("Stoch.D", 0) # Volume analysis volume = indicators.get("volume", 0) # Price levels high = indicators.get("high", 0) low = indicators.get("low", 0) open_price = indicators.get("open", 0) close_price = indicators.get("close", 0) return { "symbol": full_symbol, "exchange": exchange, "timeframe": timeframe, "timestamp": "real-time", "price_data": { "current_price": metrics['price'], "open": round(open_price, 6) if open_price else None, "high": round(high, 6) if high else None, "low": round(low, 6) if low else None, "close": round(close_price, 6) if close_price else None, "change_percent": metrics['change'], "volume": volume }, "bollinger_analysis": { "rating": metrics['rating'], "signal": metrics['signal'], "bbw": metrics['bbw'], "bb_upper": round(indicators.get("BB.upper", 0), 6), "bb_middle": round(indicators.get("SMA20", 0), 6), "bb_lower": round(indicators.get("BB.lower", 0), 6), "position": "Above Upper" if close_price > indicators.get("BB.upper", 0) else "Below Lower" if close_price < indicators.get("BB.lower", 0) else "Within Bands" }, "technical_indicators": { "rsi": round(indicators.get("RSI", 0), 2), "rsi_signal": "Overbought" if indicators.get("RSI", 0) > 70 else "Oversold" if indicators.get("RSI", 0) < 30 else "Neutral", "sma20": round(indicators.get("SMA20", 0), 6), "ema50": round(indicators.get("EMA50", 0), 6), "ema200": round(indicators.get("EMA200", 0), 6), "macd": round(macd, 6), "macd_signal": round(macd_signal, 6), "macd_divergence": round(macd - macd_signal, 6), "adx": round(adx, 2), "trend_strength": "Strong" if adx > 25 else "Weak", "stoch_k": round(stoch_k, 2), "stoch_d": round(stoch_d, 2) }, "market_sentiment": { "overall_rating": metrics['rating'], "buy_sell_signal": metrics['signal'], "volatility": "High" if metrics['bbw'] > 0.05 else "Medium" if metrics['bbw'] > 0.02 else "Low", "momentum": "Bullish" if metrics['change'] > 0 else "Bearish" } } except Exception as e: return { "error": f"Analysis failed: {str(e)}", "symbol": symbol, "exchange": exchange, "timeframe": timeframe } except Exception as e: return { "error": f"Coin analysis failed: {str(e)}", "symbol": symbol, "exchange": exchange, "timeframe": timeframe } - Helper function compute_metrics called within coin_analysis to calculate key metrics: price change, Bollinger Band width (bbw), BB rating and signal from raw indicators.
def compute_metrics(indicators: Dict) -> Optional[Dict]: try: open_price = indicators["open"] close = indicators["close"] sma = indicators["SMA20"] bb_upper = indicators["BB.upper"] bb_lower = indicators["BB.lower"] bb_middle = sma change = compute_change(open_price, close) bbw = compute_bbw(sma, bb_upper, bb_lower) rating, signal = compute_bb_rating_signal(close, bb_upper, bb_middle, bb_lower) return { "price": round(close, 4), "change": round(change, 3), "bbw": round(bbw, 4) if bbw is not None else None, "rating": rating, "signal": signal, } except (KeyError, TypeError): return None - src/tradingview_mcp/server.py:361-361 (registration)The @mcp.tool() decorator registers the coin_analysis function as an MCP tool.
@mcp.tool()