patternfetch

io.github.MarvinRey7879由 GitHub 帳號 MarvinRey7879 發布v0.3.0更新於 Oct 24, 2026

US stocks, ETFs, crypto → compact brief: patterns, S/R, regime + base rates vs baseline. Not advice.

已驗證Streamable HTTP可網頁執行金融資料與分析

概覽

AI 產生的概覽

遠端 MCP 伺服器,為助理提供美股、ETF 與加密貨幣的精簡技術面行情簡報,並附上回測的型態基準率。

可以做什麼
  • 取得單一標的與週期的精簡市場狀態簡報:K 線、帶基準率與提升度的型態、支撐壓力、市場狀態、RSI/EMA
  • 一次比較多個週期,判斷趨勢是相互印證還是背離
  • 只回傳自上次簡報以來有變動的內容(趨勢翻轉、新型態、RSI 狀態變化)
  • 找出歷史上型態相似的區間,並給出後續走勢的完整分布
  • 依市場狀態、型態或最低基準率篩選大型股、ETF 與主流加密貨幣交易對
  • 讀取伺服器本身的能力矩陣:涵蓋範圍、週期、端點、額度與價格
適用情境
適合需要在不把原始 OHLCV 塞進上下文的情況下,了解某檔股票、ETF 或加密貨幣交易對目前技術面時;也適合反覆輪詢同一市場,或先篩選候選標的再逐一分析。
執行需求
遠端 Streamable HTTP 端點,不需本機執行環境(另有可選的本機 stdio 橋接套件)。探索工具免費;呼叫工具需透過一鍵 OAuth 或 Bearer API 金鑰驗證,也可使用免金鑰的示範端點。贈送額度用完後按次從餘額扣款。
安裝前請注意
工具呼叫按次從預付餘額扣款,儲值可用信用卡或加密貨幣,反覆輪詢會產生費用。呼叫需要 API 金鑰,須妥善保管。輸出為客觀行情數據與演算法訊號,不構成投資建議;基準率不含停損、手續費與滑價。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 patternfetch,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Web executable,透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。

交給代理程式安裝

把這段提示詞貼上到 Claude Code、Codex、Cursor 等代理程式,或 SourceWeft 對話中。代理程式會讀取該伺服器的安裝指南,先向你展示發布者、端點和登入方式,經你同意後再把它新增到你的客戶端。金鑰不會寫進任何命令。

閱讀 https://sourceweft.com/mcp/io.github.MarvinRey7879%2Fpatternfetch/install.md,並按其中說明把這個 MCP 伺服器接入我的客戶端。修改任何設定之前,先告訴我它的發布者、端點和登入方式,等我確認。不要把 API 金鑰寫進命令或我會提交的檔案;問我金鑰應從哪裡取得。

檢視代理程式所依據的安裝指南

其他 MCP 客戶端

把它新增到你客戶端的 mcpServers 設定中。

{
  "mcpServers": {
    "patternfetch": {
      "type": "http",
      "url": "https://patternfetch.com/mcp"
    }
  }
}

README

patternfetch

patternfetch is a market-data API for AI agents covering US stocks, ETFs and crypto spot. One call with a ticker and a timeframe returns a token-compact market-state report: compact candles, detected chart and candlestick patterns, support and resistance levels, market regime, and interpreted indicators (RSI, EMA). Every detected pattern carries its backtested historical hit rate and its lift against the pattern-free baseline of the same market, so an agent can tell a pattern that carries information from one that does not. Six tools — brief, multi, delta, analogs, scan, capabilities — reachable over REST and MCP, with one-click OAuth, credit billing via Stripe or x402 USDC on Base, a keyless demo endpoint, and $3 starter credit on signup. Impersonal market data, not investment advice.

[npm] [patternfetch MCP server] [license]

Why it's smaller: for BTC/USDT 4h (120 candles), a raw OHLCV dump is ~3,260 tokens of just numbers the model still has to analyze; patternfetch's interpreted analysis is ~1,323 tokens, already decided. Reproduce it (no account needed).

  • Coverage: US stocks and ETFs (split- and dividend-adjusted, delayed/EOD, via Yahoo), crypto spot (realtime, via Binance).
  • Timeframes: 1m, 5m, 15m, 30m, 1h, 4h, 1d, 1w.
  • Access: REST at patternfetch.com/v1/*, MCP at patternfetch.com/mcp (Streamable HTTP), plus a local stdio bridge (patternfetch-mcp).

Why base rates and lift

A detector that only reports double_top, confidence 0.92 tells an agent nothing about whether that pattern has ever meant anything. patternfetch attaches an evidence block to each detected pattern:

json
{  "name": "double_top",  "confidence": 0.92,  "evidence": {    "scope": "US stocks & ETFs",    "tf": "1d",    "band": "0.75-1.00",    "horizon": 10,    "n": 7508,    "hitRate": 0.431,    "ci95": 0.011,    "lift": {      "baseline": 0.419979,      "baselineN": 46038,      "lift": 0.011021,      "ci95": 0.012075,      "informative": false,      "reading": "indistinguishable-from-baseline"    }  }}

hitRate is the realizable gross directional base rate: the fraction of non-overlapping historical occurrences of that pattern, in that timeframe and confidence band, whose close-to-close return over the next horizon bars went the expected direction. The forward window starts at detection, so there is no lookahead. No stops, fees or slippage are modelled.

lift compares that hit rate against the baseline of the same market with no pattern present. Many patterns come back indistinguishable-from-baseline — that is the honest result, and reporting it is the point. An agent can filter on informative instead of trusting a geometric confidence score.

Calibration. Across 105 audited categories, 3 fall outside their confidence interval — fewer than the ~5.3 that chance alone predicts across 105 comparisons. For US stocks it is 0 of 60. Method and full tables: patternfetch.com/pattern-base-rates-study. The measurement is reproducible with the open-source honest-signals tool.

Quickstart

No key required — the demo endpoint is public:

bash
curl -X POST https://patternfetch.com/v1/demo \  -H 'content-type: application/json' \  -d '{"ticker":"AAPL","timeframe":"1d"}'

With a key (self-serve, $3 starter credit):

bash
curl -X POST https://patternfetch.com/v1/keys -d '{"email":"[email protected]"}'
curl -X POST https://patternfetch.com/v1/brief \  -H 'authorization: Bearer pf_...' \  -H 'content-type: application/json' \  -d '{"ticker":"BTC/USDT","timeframe":"4h"}'

JavaScript client:

bash
npm install patternfetch
js
import { Patternfetch } from 'patternfetch';
const { key } = await new Patternfetch().createKey('[email protected]');const pf = new Patternfetch({ apiKey: key });
const brief = await pf.brief({ ticker: 'AAPL', timeframe: '1d' });
console.log(brief.analysis.nl);// "AAPL: uptrend (strong), +0.14% last 1d, RSI 71.66 (overbought),//  bearish_engulfing (conf 1, hist 41% over 10b, lift -0.7pp vs 42% base (within noise))."
for (const p of brief.analysis.patterns) {  if (p.evidence?.lift.informative) console.log(p.name, p.evidence.hitRate, p.evidence.lift.lift);}

Tools

Six tools, the same set over MCP (patternfetch_*) and REST (POST /v1/*).

ToolWhat it returnsWhen an agent calls it
briefMarket-state report for one ticker + timeframe: compact candles, patterns with base rate and lift, support/resistance, regime, RSI/EMA, one-line summary.The default. It needs the current technical picture of one market without dumping raw OHLCV into context.
multiOne brief per timeframe (default 1h, 4h, 1d) plus a cross-timeframe alignment read that spells out agreement or divergence, e.g. 1h up / 4h up / 1d down.It wants to know whether a setup is confirmed or contradicted across horizons, without three separate brief calls.
deltaOnly what changed since the last brief for that ticker + timeframe — trend flips, new patterns, RSI-state changes. Returns changed: false when nothing material moved.It polls the same market repeatedly. Call brief once, then delta on every later poll to keep token cost near zero.
analogsHistorical windows whose shape resembles current price action, with the full distribution of what followed: win rate, median, mean, min, max and n over a fixed forward horizon.It wants the historical outcome spread for a setup rather than a point estimate. Not a prediction, not a strategy backtest.
scanScreener over a curated universe of liquid US large-caps, core and sector ETFs and major crypto pairs. Filter by asset class, regime, pattern and minimum base rate; rows return ranked by base rate with 95% CI. Precomputed daily.It needs to find candidates across the market rather than analyse a ticker it already named. Feed the shortlist into brief.
capabilitiesSupported assets, timeframes, endpoints, limits and pricing. No input.First, before relying on any assumption about coverage.

Client methods

MethodEndpoint
brief({ticker, timeframe, limit?, fields?, market?})POST /v1/brief
multi({ticker, timeframes?, limit?, market?})POST /v1/multi
delta({ticker, timeframe, limit?})POST /v1/delta
analogs({ticker, timeframe, window?, horizon?})POST /v1/analogs
scan({assetClass?, regime?, pattern?, tf?, minBaseRate?, limit?})POST /v1/scan
candles({ticker, timeframe})POST /v1/candles
platforms()GET /v1/platforms
createKey(email)POST /v1/keys

MCP

patternfetch is a remote MCP server (Streamable HTTP) at https://patternfetch.com/mcp. Tools: patternfetch_brief, patternfetch_multi, patternfetch_delta, patternfetch_analogs, patternfetch_scan, patternfetch_capabilities. Discovery (initialize, tools/list) is free — no key. Only tools/call needs auth.

One-click OAuth (nothing to paste) — in Claude Code, Claude Desktop, Cursor or Smithery, add the URL and authorize once; a free-tier key is minted for you:

bash
claude mcp add --transport http patternfetch https://patternfetch.com/mcp

In claude.ai: Customize → Connectors → Add custom connector → https://patternfetch.com/mcp → Authorize.

Or with a Bearer key — add to your MCP config:

json
{  "mcpServers": {    "patternfetch": {      "url": "https://patternfetch.com/mcp",      "headers": { "Authorization": "Bearer pf_..." }    }  }}

Get a free key (small starter credit) at https://patternfetch.com/v1/keys.

Local stdio bridge

Prefer a local stdio server (Claude Desktop, sandboxes, no inbound HTTP)? This package ships patternfetch-mcp, a zero-dependency stdio↔HTTP bridge that exposes the same tools and forwards calls to patternfetch.com:

json
{  "mcpServers": {    "patternfetch": {      "command": "npx",      "args": ["-y", "patternfetch-mcp"],      "env": { "PATTERNFETCH_API_KEY": "pf_..." }    }  }}

tools/list works with no key and falls back to the embedded snapshot (mcp-tools.json) when the remote is unreachable, so introspection always succeeds. Tool calls use PATTERNFETCH_API_KEY, OAuth or x402. Override the endpoint with PATTERNFETCH_MCP_URL.

Refresh the snapshot from the live server:

bash
curl -s -X POST https://patternfetch.com/mcp \  -H 'content-type: application/json' \  -H 'accept: application/json, text/event-stream' \  -d '{"jsonrpc":"2.0","id":1,"method":"tools/list"}'

Pricing

$3 starter credit on signup, at least $0.50 of it usable immediately without a card. After that, pay per call from credit, topped up via Stripe or x402 USDC on Base. Studio plan: $19/month including $25 of usage.

CallPrice
/v1/brief$0.010
/v1/multi$0.025
/v1/delta$0.008 ($0.001 when nothing changed)
/v1/candles$0.005
/v1/analogs$0.050
/v1/scan$0.020

Live figures: GET /v1/platforms.

Legal

patternfetch provides impersonal market data and algorithmic signals for informational purposes only. NOT investment, financial, legal or tax advice, and not a recommendation to buy, sell or hold any security or crypto-asset. Outputs are not personalized to you. Base rates are gross directional frequencies without stops, fees or slippage; past performance and historical analogs do not guarantee future results. Markets are volatile — you may lose all capital. Do your own research. See patternfetch.com/disclaimer, /methodology and /terms.

來源:README.md,提交 15116eb

工具

6

patternfetch_brief

Market-State Brief

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.

輸入參數limitmarketticker必填timeframe必填

patternfetch_multi

Multi-Timeframe Brief

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.

輸入參數limitmarketticker必填timeframes

patternfetch_delta

What Changed Since Last Brief

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.

輸入參數limitmarketticker必填timeframe必填

patternfetch_analogs

Historical Analogs Distribution

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.

輸入參數marketticker必填windowhorizontimeframe必填

patternfetch_scan

Pattern & Regime Screener

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

輸入參數tflimitregimeminLiftpatternassetClassminBaseRate

patternfetch_capabilities

Server 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).

無需輸入參數。

版本歷史

1
  1. v0.3.0最新Sep 16, 2026

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