patternfetch MCP server

• patternfetch_analogsFree

  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.

• patternfetch_briefFree

  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.

• patternfetch_capabilitiesFree

  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).

• patternfetch_deltaFree

  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.

• patternfetch_multiFree

  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.

• patternfetch_scanFree

  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.

• –Code scanremote-only server, no package to scann/a
• Live reliabilityremote reachable in 1416ms20/20
• Tool poisoning6 tool descriptions checked13/15
• Auth qualityopen endpoint, read-only tools10/15
• Maintenancelast push 69 days ago12/15
• Maintainer identityregistry namespace matches repository owner; GitHub account older than a year8/10

Safety score

84/100

higher than 78% of 1,761 Finance servers

Tools

6

the typical Finance server has 8

Tools that change things

0%

typical: 0%. Fewer write tools means less an agent can break

Uptime

100%

of our recent checks; the typical remote Finance server answers 100%

Response time

107 ms

faster than 86% of 1,133 Finance servers

patternfetch: common questions

Is patternfetch MCP server safe?

Mostly: it is graded B (84/100). Read the patternfetch safety report

How do I install patternfetch?

It runs remotely at patternfetch.com. Add it to Claude Code, Cursor, VS Code or Claude Desktop with the snippets above, or call it through the mcp.market gateway without installing anything.

Does patternfetch need an API key?

Not as far as the registry entry and our scan can tell: no credentials are declared or required.

Is patternfetch maintained?

The last commit was 109 days ago (2026-07-18). The latest release is v0.3.0.

Is patternfetch up?

100% of our last 28 checks got an answer. We check remote servers about four times a day.

What can I use instead of patternfetch?

Servers from other publishers that do the same job: Shumi MCP server, Alpha Vantage MCP server and TickDB Market Data MCP server.

How does patternfetch compare with other Finance MCP servers?

safety score 84/100 (higher than 78% of 1,761 Finance servers); tools 6 (the typical Finance server has 8); tools that change things 0% (typical: 0%. Fewer write tools means less an agent can break). Full comparison.