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sh.kwant/kwant

sh.kwant/kwant · v1.0.0

Measured by MCP Station

Description written by the publisher, not verified

Quant intelligence over MCP: backtest, signals, screens, scores & portfolios for US & TSX stocks.

Connect

claude mcp add --transport http kwant https://kwant.sh/mcp

{
  "mcpServers": {
    "kwant": {
      "url": "https://kwant.sh/mcp"
    }
  }
}

Tools as reported by the server

• get_price_history
  Get historical OHLCV price bars for a ticker. US symbols are bare (AAPL, MSFT); TSX symbols use the Yahoo .TO form (RY.TO) or the TSX:RY form. interval is one of 1m,5m,15m,30m,1h,1d,1wk,1mo (default 1d); range is one of 5d,1mo,3mo,6mo,1y,2y,5y,max (default 1y). Returns an envelope whose values conta
• get_quote
  Get the latest available quote for a ticker. US symbols are bare (AAPL); TSX symbols use the Yahoo .TO form (RY.TO) or the TSX:RY form. Returns an envelope whose values holds the quote fields (price, currency, previous_close, change, change_percent, volume, market_state, asof as an ISO string). (pai
• get_fundamentals
  Get fundamental data for a ticker (profile + key ratios). US symbols are bare (AAPL); TSX symbols use the Yahoo .TO form (RY.TO) or the TSX:RY form. Returns an envelope whose values holds available fundamentals: name, exchange, currency, sector, industry, market_cap, pe_ratio, forward_pe, eps, divid
• compute_indicator
  Compute a technical indicator (RSI, MACD, SMA, EMA, BBANDS, ATR, ADX, STOCH) over a ticker's price history. Returns the warmup-aligned series plus the latest values and a one-line summary. Tune the window with `length` (SMA/EMA/RSI/ATR/ADX/BBANDS), `fast`/`slow`/`signal` (MACD), `std` (BBANDS), or `
• detect_signals
  Detect classic technical-analysis signals on a ticker's price history. Each requested signal is evaluated and reported as triggered/not-triggered with a date and human-readable detail under signal_summary. Signals (omit `signals` to check all six): golden_cross = SMA(50) crosses above SMA(200) withi
• compute_stats
  Compute quantitative statistics (volatility, sharpe, max_drawdown, returns, beta, correlation) over a ticker's daily price history. Omit `metrics` to default to volatility/sharpe/max_drawdown/returns. `beta` and `correlation` require a `benchmark` ticker; `risk_free_rate` is used only by the Sharpe
• compare_tickers
  Rank two or more tickers against each other by a single metric (total_return, volatility, sharpe, max_drawdown, last_price). Symbols that cannot be resolved (or lack enough history) are skipped and noted in `warnings` rather than failing the call. Returns a ranked list of {ticker, value, rank, curre
• screen
  Screen a stock universe for tickers matching quantitative filters (logical AND). Fields: price, rsi, sma_50, sma_200, volatility, sharpe, max_drawdown, total_return, dollar_volume, garman_klass_vol. Ops: lt, lte, gt, gte. (paid: $0.0100/call)
• backtest
  Backtest a simple long-only technical strategy on daily price history. Strategies: sma_cross (golden/death cross of SMA 50/200), rsi_reversion (enter RSI<30, exit RSI>70), macd_cross (MACD line vs signal). No-lookahead: signals act on the next bar's close. Returns trades + performance metrics. (paid
• screen_with_scores
  Rank a stock universe by a continuous cross-sectional signal score (rank 1 = highest z-score). Signals: jt_momentum, mean_reversion, rsi_filtered_momentum, trend_quality. Scores are relative to the scanned set. (paid: $0.0100/call)
• compute_universe_scores
  Score and rank a universe of tickers by a cross-sectional signal. Resolves either a named universe (SP500, TSX) or an explicit tickers override, bulk-fetches daily price history over range, computes a raw per-ticker score for the chosen signal, then converts those raw scores into cross-sectional z-s
• build_monthly_universe
  Rank a universe of tickers by monthly dollar volume with trailing returns. Resolves either a named universe (SP500, TSX) or an explicit tickers override, bulk-fetches daily OHLCV over range, resamples each to monthly bars (open=first, high=max, low=min, close=last, volume=sum), and per ticker comput
• construct_portfolio
  Turn a {ticker: score} mapping into long-only portfolio weights. Selects names and assigns non-negative weights that sum to 1.0 using the chosen method: top_n_weighted (weight by clipped score), equal_weight, risk_parity (inverse-volatility), concentrated_vol (highest-vol from a top-score pool), or
• run_portfolio_backtest
  Backtest a rebalanced, multi-ticker, long-only quant portfolio. Fetches daily history for every ticker over range, then runs a walk-forward simulation: at each period-end rebalance the chosen signal (jt_momentum, mean_reversion, rsi_filtered_momentum, trend_quality) scores each name using only data
• compute_portfolio_stats
  Compute portfolio-level statistics for a weighted basket of tickers. Given a {ticker: weight} mapping, fetches each ticker's daily history over range and returns the portfolio-level (not per-ticker) volatility, sharpe, max_drawdown and total_return of the weighted basket. weights need NOT sum to 1 (
• compute_correlation_matrix
  Compute the pairwise return-correlation matrix for a list of tickers. Fetches each ticker's daily history over range, converts it to daily returns, and computes the pairwise Pearson correlation (aligned on shared dates). Requires at least two tickers; tickers that cannot be fetched are dropped and n

Website · JSON · Text for agents · Registry updated 2026-07-07