patternfetch
US stocks, ETFs, crypto → compact brief: patterns, S/R, regime + base rates vs baseline. Not advice.
我該用這個嗎
品質與安全性
發現項目(1)
- LOW在 patternfetch_capabilities 中
根據工具定義與協定合規性的自動化分析。
上下文成本
這是每次將伺服器的工具載入模型上下文時所消耗的約略 token 數量。數量越高,可用於其他工作的注意力就越少。
安裝
一鍵安裝
將以下內容加入你的 `claude_desktop_config.json` 檔案:
{
"mcpServers": {
"patternfetch": {
"url": "https://patternfetch.com/mcp"
}
}
}遠端端點
https://patternfetch.com/mcpstreamable-http它能做什麼
工具清單
工具(6)
🟢patternfetch_brief(ticker, timeframe, limit, market)
Get a token-compact market-state brief for a stock, ETF, or crypto ticker + timeframe. Returns compact candles, detected chart/candlestick patterns with geometric confidence AND a backtested historical base rate (how often that pattern+timeframe+confidence-band actually resolved its way), support/resistance levels, trend/regime, and interpreted indicators (RSI/EMA state) plus a one-line summary. Covers US stocks/ETFs (split & dividend adjusted, delayed/EOD) and crypto spot (realtime). WHEN: an agent needs the current technical picture of a market without dumping raw OHLCV into context (saves tokens, avoids numeric hallucination). WHEN NOT: you need order execution or portfolio advice. Examples: {"ticker":"AAPL","timeframe":"1d"}, {"ticker":"BTC/USDT","timeframe":"4h"}. Output is impersonal market data, NOT investment advice.
輸入結構描述
{
"type": "object",
"properties": {
"ticker": {
"type": "string",
"description": "Symbol to analyse. US stock or ETF like \"AAPL\" / \"SPY\", or a crypto spot pair like \"BTC/USDT\". Always spell crypto as a pair: a bare \"BTC\" or \"ETH\" is a real US-listed ETF, NOT the coin, and it will return that ETF's prices without failing. Affected responses carry a \"notice\" field."
},
"timeframe": {
"type": "string",
"description": "Bar size. One of 1m, 5m, 15m, 30m, 1h, 4h, 1d, 1w. Coverage differs per asset class — see the capabilities tool."
},
"limit": {
"type": "integer",
"description": "How many recent bars to analyse: integer >= 20, capped at 1000, default 200. Fewer bars = fewer tokens."
},
"market": {
"type": "string",
"enum": [
"crypto",
"stock"
],
"description": "Optional asset-class override. Omit and it is inferred from the ticker: a \"BASE/QUOTE\" pair is crypto, a plain symbol is a US stock/ETF."
}
},
"required": [
"ticker",
"timeframe"
]
}🟢patternfetch_multi(ticker, timeframes, limit, market)
Get a multi-timeframe market-state view for one stock, ETF, or crypto ticker in a single call: a token-compact brief for each requested timeframe (default 1h, 4h, 1d) PLUS a cross-timeframe alignment read — whether the trends across timeframes agree or diverge, with the split spelled out (e.g. "1h up / 4h up / 1d down"). WHEN: an agent wants to know if a setup is confirmed across horizons or conflicting between them, without making 3 separate brief calls. WHEN NOT: you only care about one timeframe (use brief). The alignment/divergence is impersonal DESCRIPTIVE data, not a signal to act on. Example: {"ticker":"BTC/USDT","timeframes":["1h","4h","1d"]}. Not investment advice.
輸入結構描述
{
"type": "object",
"properties": {
"ticker": {
"type": "string",
"description": "Symbol to analyse. US stock or ETF like \"AAPL\" / \"SPY\", or a crypto spot pair like \"BTC/USDT\". Always spell crypto as a pair: a bare \"BTC\" or \"ETH\" is a real US-listed ETF, NOT the coin, and it will return that ETF's prices without failing. Affected responses carry a \"notice\" field."
},
"timeframes": {
"type": "array",
"items": {
"type": "string"
},
"description": "Bar sizes to compare, at most 4, e.g. [\"1h\",\"4h\",\"1d\"]. Defaults to [\"1h\",\"4h\",\"1d\"] when omitted."
},
"limit": {
"type": "integer",
"description": "How many recent bars to analyse: integer >= 20, capped at 1000, default 200. Fewer bars = fewer tokens."
},
"market": {
"type": "string",
"enum": [
"crypto",
"stock"
],
"description": "Optional asset-class override. Omit and it is inferred from the ticker: a \"BASE/QUOTE\" pair is crypto, a plain symbol is a US stock/ETF."
}
},
"required": [
"ticker"
]
}🟢patternfetch_delta(ticker, timeframe, limit, market)
Get only what CHANGED since your last brief for a ticker+timeframe (trend flips, new patterns, RSI-state changes). WHEN: an agent polls the same market repeatedly and wants minimal tokens — call brief once, then delta on each later poll. WHEN NOT: first look at a market (use brief). Returns changed=false when nothing material changed. Example: {"ticker":"BTC/USDT","timeframe":"4h"}. Impersonal data, not advice.
輸入結構描述
{
"type": "object",
"properties": {
"ticker": {
"type": "string",
"description": "Symbol to analyse. US stock or ETF like \"AAPL\" / \"SPY\", or a crypto spot pair like \"BTC/USDT\". Always spell crypto as a pair: a bare \"BTC\" or \"ETH\" is a real US-listed ETF, NOT the coin, and it will return that ETF's prices without failing. Affected responses carry a \"notice\" field."
},
"timeframe": {
"type": "string",
"description": "Bar size. One of 1m, 5m, 15m, 30m, 1h, 4h, 1d, 1w. Coverage differs per asset class — see the capabilities tool."
},
"limit": {
"type": "integer",
"description": "How many recent bars to analyse: integer >= 20, capped at 1000, default 200. Fewer bars = fewer tokens."
},
"market": {
"type": "string",
"enum": [
"crypto",
"stock"
],
"description": "Optional asset-class override. Omit and it is inferred from the ticker: a \"BASE/QUOTE\" pair is crypto, a plain symbol is a US stock/ETF."
}
},
"required": [
"ticker",
"timeframe"
]
}🟢patternfetch_analogs(ticker, timeframe, window, horizon, market)
Find earlier windows IN THE SAME SERIES whose shape resembles the current price action and return the FULL distribution of what followed (win-rate, median, min, max, n) over a fixed forward horizon. Parameters: window = how many recent bars form the shape being matched (default 32); horizon = how many bars forward each match is measured over (default 20). WHEN: an agent wants the historical spread of outcomes after a similar-looking setup, including how wide and how uncertain that spread is. WHEN NOT: you want the current technical picture (use brief), you want to find candidates across the market (use scan), or you need one expected value — this deliberately returns a distribution, not a point estimate. NOT a prediction, NOT a backtest of a strategy; past distribution does not guarantee future results. Example: {"ticker":"ETH/USDT","timeframe":"1d"}. Impersonal data, not advice.
輸入結構描述
{
"type": "object",
"properties": {
"ticker": {
"type": "string",
"description": "Symbol to analyse. US stock or ETF like \"AAPL\" / \"SPY\", or a crypto spot pair like \"BTC/USDT\". Always spell crypto as a pair: a bare \"BTC\" or \"ETH\" is a real US-listed ETF, NOT the coin, and it will return that ETF's prices without failing. Affected responses carry a \"notice\" field."
},
"timeframe": {
"type": "string",
"description": "Bar size. One of 1m, 5m, 15m, 30m, 1h, 4h, 1d, 1w. Coverage differs per asset class — see the capabilities tool."
},
"window": {
"type": "integer",
"description": "Number of recent bars forming the shape matched against history. Default 32."
},
"horizon": {
"type": "integer",
"description": "Number of bars forward over which the outcome after each match is measured. Default 20."
},
"market": {
"type": "string",
"enum": [
"crypto",
"stock"
],
"description": "Optional asset-class override. Omit and it is inferred from the ticker: a \"BASE/QUOTE\" pair is crypto, a plain symbol is a US stock/ETF."
}
},
"required": [
"ticker",
"timeframe"
]
}🟢patternfetch_scan(assetClass, regime, pattern, tf, minBaseRate, ...)
Scan US stocks, ETFs, and crypto for tickers currently in a given regime or showing a chart/candlestick pattern, RANKED by the honest backtested base rate + 95% CI — discovery, NOT lookup. This is the screener: instead of asking about one ticker you already know, ask "which tickers right now are in an uptrend / printing a double_bottom, and which of those has the strongest historical base rate?" and get a ranked shortlist back. Precomputed daily over a curated universe (liquid US large-caps + core/sector ETFs + major crypto pairs) so it is fast and cheap. Filters (all optional): assetClass ("stock"|"crypto"|"all"), regime ("up"|"down"|"range"), pattern (e.g. "double_bottom","double_top","head_and_shoulders","bullish_engulfing","bearish_engulfing","hammer"), minLift (-1..1 in rate points, e.g. 0.02 = keep only patterns beating their OWN pattern-free baseline by >= 2pp; 0 = at or above baseline), minBaseRate (0..1, drop tickers whose top pattern base rate is below this), tf, limit. PREFER minLift over minBaseRate: a raw base rate is not comparable across bullish and bearish rows, so minBaseRate:0.55 mostly returns bullish patterns in a rising universe before any of them carries information, whereas minLift returns the ones that measurably add something. Rows with no baseline in the evidence table are excluded by any minLift (absence of a lift is not a lift of 0). Each row: {sym, tf, assetClass, regime, pattern, baseRate, ci95, n, scope, confidence, asOf} PLUS the drift-free comparison {baseline, lift, liftCi95, liftReading} — baseline is the direction-matched rate with no pattern present, lift is baseRate minus that baseline, and liftReading says whether the difference is distinguishable from zero at all ("above-baseline" | "below-baseline" | "indistinguishable-from-baseline"). Read lift, not baseRate, when comparing a bullish row against a bearish one: in a rising universe a bullish pattern starts ahead before it carries any information. Ranked by baseRate desc, then confidence desc, then narrower CI, then fresher asOf. WHEN: an agent wants to FIND candidates across the market, not analyze a named one (then call brief on the shortlist). WHEN NOT: you already have a specific ticker (use brief). Example: {"assetClass":"all","regime":"up","minLift":0.02,"limit":20}. Impersonal historical data, not investment advice; base rates are gross directional frequencies and do not guarantee future results.
輸入結構描述
{
"type": "object",
"properties": {
"assetClass": {
"type": "string",
"enum": [
"stock",
"crypto",
"all"
],
"description": "Restrict the scanned universe. Default \"all\"."
},
"regime": {
"type": "string",
"enum": [
"up",
"down",
"range"
],
"description": "Only return tickers currently in this regime. Omit for any."
},
"pattern": {
"type": "string",
"description": "Only return tickers whose top pattern is this one, e.g. \"double_bottom\", \"double_top\", \"head_and_shoulders\", \"bullish_engulfing\", \"bearish_engulfing\", \"hammer\"."
},
"tf": {
"type": "string",
"enum": [
"1m",
"5m",
"15m",
"30m",
"1h",
"4h",
"1d",
"1w"
],
"description": "Only return signals precomputed on this bar size. Omit to consider every precomputed timeframe."
},
"minBaseRate": {
"type": "number",
"minimum": 0,
"maximum": 1,
"description": "Number in [0,1]. Drop tickers whose top pattern base rate is below this threshold. CAUTION: a raw base rate is NOT comparable across bullish and bearish rows — in a rising universe a bullish pattern clears a high threshold on drift alone, before it carries any information. Prefer minLift for an unbiased shortlist."
},
"minLift": {
"type": "number",
"minimum": -1,
"maximum": 1,
"description": "Number in [-1,1], in rate points (0.02 = 2pp). Drop tickers whose top pattern does not beat its OWN pattern-free baseline by at least this much. This is the drift-free filter and the one to reach for: minBaseRate:0.55 mostly selects bullish patterns in a rising market, whereas minLift:0.02 selects patterns that actually add something. minLift:0 means \"at or above baseline\". Negative values are allowed. Rows whose evidence carries no baseline are always excluded — absence of a lift is not a lift of 0."
},
"limit": {
"type": "integer",
"description": "Maximum rows to return: integer in [1,500], default 50."
}
}
}🟢patternfetch_capabilities
Return patternfetch's own capability matrix: which asset classes are covered (US stocks, ETFs, crypto spot), the data source and delay for each, the supported timeframes, the endpoint list, the per-call prices and tier limits, and the product version. Takes no arguments and returns the same static self-description on every call — it contains NO market data (no quotes, candles, patterns or base rates). WHEN: once at the start of a session, to learn which asset classes and timeframes are supported before calling brief/multi/delta/analogs/scan, instead of guessing and getting a validation error. WHEN NOT: you already know the ticker and timeframe are supported (go straight to brief), or you want actual market data (this returns none).
輸入結構描述
{
"type": "object",
"properties": {}
}社群
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