TradingView MCP Server

Instructions

Implementation Reference

• src/tradingview_mcp/server.py:296-312 (handler)

  The @mcp.tool()-decorated handler function for 'top_losers'. Sanitizes inputs, calls _fetch_trending_analysis to get trending coins, sorts by changePercent ascending (lowest first for losers), limits, and formats output as list of dicts with symbol, changePercent, and indicators.
  @mcp.tool() def top_losers(exchange: str = "KUCOIN", timeframe: str = "15m", limit: int = 25) -> list[dict]: """Return top losers for an exchange and timeframe using bollinger band analysis.""" exchange = sanitize_exchange(exchange, "KUCOIN") timeframe = sanitize_timeframe(timeframe, "15m") limit = max(1, min(limit, 50)) rows = _fetch_trending_analysis(exchange, timeframe=timeframe, limit=limit) # Reverse sort for losers (lowest change first) rows.sort(key=lambda x: x["changePercent"]) # Convert to dict format return [{ "symbol": row["symbol"], "changePercent": row["changePercent"], "indicators": dict(row["indicators"]) } for row in rows[:limit]]
• src/tradingview_mcp/server.py:146-208 (helper)

  Core helper function called by top_losers (and top_gainers). Loads symbols, fetches TA analysis in batches from TradingView, computes metrics including changePercent via compute_metrics, applies optional filters, sorts by changePercent descending, returns top limit Rows.
  def _fetch_trending_analysis(exchange: str, timeframe: str = "5m", filter_type: str = "", rating_filter: int = None, limit: int = 50) -> List[Row]: """Fetch trending coins analysis similar to the original app's trending endpoint.""" if not TRADINGVIEW_TA_AVAILABLE: raise RuntimeError("tradingview_ta is missing; run `uv sync`.") symbols = load_symbols(exchange) if not symbols: raise RuntimeError(f"No symbols found for exchange: {exchange}") # Process symbols in batches due to TradingView API limits batch_size = 200 # Considering API limitations all_coins = [] screener = EXCHANGE_SCREENER.get(exchange, "crypto") # Process symbols in batches for i in range(0, len(symbols), batch_size): batch_symbols = symbols[i:i + batch_size] try: analysis = get_multiple_analysis(screener=screener, interval=timeframe, symbols=batch_symbols) except Exception as e: continue # If this batch fails, move to the next one # Process coins in this batch for key, value in analysis.items(): try: if value is None: continue indicators = value.indicators metrics = compute_metrics(indicators) if not metrics or metrics.get('bbw') is None: continue # Apply rating filter if specified if filter_type == "rating" and rating_filter is not None: if metrics['rating'] != rating_filter: continue all_coins.append(Row( symbol=key, changePercent=metrics['change'], indicators=IndicatorMap( open=metrics.get('open'), close=metrics.get('price'), SMA20=indicators.get("SMA20"), BB_upper=indicators.get("BB.upper"), BB_lower=indicators.get("BB.lower"), EMA50=indicators.get("EMA50"), RSI=indicators.get("RSI"), volume=indicators.get("volume"), ) )) except (TypeError, ZeroDivisionError, KeyError): continue # Sort all coins by change percentage all_coins.sort(key=lambda x: x["changePercent"], reverse=True) return all_coins[:limit]
• src/tradingview_mcp/server.py:28-42 (schema)

  TypedDict definitions for IndicatorMap (indicators data) and Row (output row structure: symbol, changePercent, indicators) used by top_losers output format.
  class IndicatorMap(TypedDict, total=False): open: Optional[float] close: Optional[float] SMA20: Optional[float] BB_upper: Optional[float] BB_lower: Optional[float] EMA50: Optional[float] RSI: Optional[float] volume: Optional[float] class Row(TypedDict): symbol: str changePercent: float indicators: IndicatorMap
• src/tradingview_mcp/server.py:268-271 (registration)

  FastMCP server initialization where top_losers is listed among available tools in the instructions.
  mcp = FastMCP( name="TradingView Screener", instructions=("Crypto screener utilities backed by TradingView Screener. Tools: top_gainers, top_losers, multi_changes."), )