MCP server

Kwant Official

sh.kwant/kwant

Checked 26 Oct 2026, 08:29 UTC · Connected to it and listed its tools

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

Website

At a glance

Type

MCP server

Publisher

kwant.sh (verified by the MCP Registry)

Status

Working at last check

Tools

16

Token cost

About 4,841 tokens per request

Sets up in

Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok

Last checked

26 Oct 2026, 08:29 UTC

Connect it to your agent

Add to CursorAdd to VS CodeVS Code Insiders

Opens the app, which shows the server and asks you to confirm. For other apps, copy the setup below.

Claude Code

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

Claude Desktop

Settings → Connectors → Add custom connector, and paste the URL.

Codex (config.toml)

[mcp_servers.kwant]
url = "https://kwant.sh/mcp"

Gemini CLI

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

Cursor

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

VS Code

{"servers":{"kwant":{"type":"http","url":"https://kwant.sh/mcp"}}}

Antigravity

agy mcp add kwant https://kwant.sh/mcp

ChatGPT

Settings → Apps & Connectors → Advanced settings: turn on Developer mode, then Create a connector and paste the URL. Which plans can do this varies.

OpenAI API (Responses tools)

{"type":"mcp","server_label":"kwant","server_url":"https://kwant.sh/mcp","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"kwant","server_url":"https://kwant.sh/mcp"}

Tools

• backtest ~223 tokens
  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
• build_monthly_universe ~401 tokens
  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
• compare_tickers ~232 tokens
  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
• compute_correlation_matrix ~246 tokens
  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
• compute_indicator ~497 tokens
  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 `
• compute_portfolio_stats ~286 tokens
  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_stats ~253 tokens
  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
• compute_universe_scores ~456 tokens
  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
• construct_portfolio ~315 tokens
  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
• detect_signals ~386 tokens
  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
• get_fundamentals ~186 tokens
  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
• get_price_history ~235 tokens
  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 ~152 tokens
  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
• run_portfolio_backtest ~434 tokens
  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
• screen ~312 tokens
  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)
• screen_with_scores ~227 tokens
  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)

Browse

• Website monitoring
• Stocks and markets
• Government and public data

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