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  1. Home
  2. πŸ’° Finance & Fintech
  3. Patternfetch
Patternfetch logo
Health: ActiveRecent health check succeeded.Last checked 9/22/2026, 7:17:19 PM

Patternfetch

User RatingsBe the first to rate and review this MCP server! Enrichment pendingWe haven’t run our AI enrichment pass on this listing yet, so the overview, use cases, and FAQ below may be sparse or missing. We work through the catalog over time β€” check back soon.
View RepositoryVisit Website

Crypto ticker+timeframe β†’ compact market-state brief (patterns, S/R, regime). Not advice.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β€” or use 1-click editor setup below.

Add to CursorAdd to VS Code
Not yet automatically verified

We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag β€” we're steadily working through the catalog.

Manual Client & Custom JSON ConfigExpand JSON β–Ύ

Client Config & Setup

Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "patternfetch": {
      "command": "npx",
      "args": [
        "-y",
        "patternfetch-mcp"
      ]
    }
  }
}

πŸ’‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Tool Schemas (6) Directory Badge Claim listing AlternativesπŸ’° More in Finance & Fintech

Capabilities & Tool Schemas (6) ~171 tokensApproximate context cost of this server’s tool schemas (~4 chars/token), before any tool is called. Actual usage depends on your client and model.Self-reported Self-reportedParsed from the repository README, not verified against a live server β€” may be incomplete or out of date.

Inspect callable tools, capabilities, and parameters exposed to AI agents by Patternfetch.

brief

The default. It needs the current technical picture of one market without dumping raw OHLCV into context.

multi

It wants to know whether a setup is confirmed or contradicted across horizons, without three separate `brief` calls.

delta

It polls the same market repeatedly. Call `brief` once, then `delta` on every later poll to keep token cost near zero.

analogs

It wants the historical outcome spread for a setup rather than a point estimate. Not a prediction, not a strategy backtest.

scan

It needs to *find* candidates across the market rather than analyse a ticker it already named. Feed the shortlist into `brief`.

capabilities

First, before relying on any assumption about coverage.

Documentation Overview

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 β€” brief, multi, delta, analogs, scan, capabilities β€” 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:

config.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 β€” 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 β€” 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 β€” the demo endpoint is public:

Terminal
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):

Terminal
curl -X POST https://patternfetch.com/v1/keys -d '{"email":"you@example.com"}'

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:

Terminal
npm install patternfetch
server.ts
import { Patternfetch } from 'patternfetch';

const { key } = await new Patternfetch().createKey('you@example.com');
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 β€” 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 β€” no key. Only tools/call needs auth.

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

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

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

Or with a Bearer key β€” add to your MCP config:

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:

config.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:

Terminal
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

Read the full README β†’View source on GitHub β†’

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Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks β€” not a rating.

npm downloads
39
Package downloads in the last 30 days.
Last commit
2mo ago
Most recent push to the default branch.
Tools exposed
6
Callable tools this server registers over MCP.
Directory activity
2 views
Config copies, upvotes, and views on AllMCPs.

Reviews

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Frequently Asked Questions about Patternfetch

Add the following block to your claude_desktop_config.json under mcpServers: "mcpServers": { "patternfetch": { "command": "npx", "args": ["-y","patternfetch-mcp"] } }

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Technical Specs & Signals

CategoryπŸ’°Finance & Fintech
More technical detailsExpand β–Ύ
TransportSTDIO
RuntimeNode.js
Last updatedJul 18, 2026
4/9 checks healthy over the last 46d
Views2
Unique ViewsTotal visits recorded for this listing page on AllMCPs.
Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars0
GitHub Star CountTotal stargazers on GitHub representing community popularity (0 stars).
Last commit2mo ago
Last Repository CommitThe most recent commit or push recorded for this server's GitHub repository.Last commit on Jul 18, 2026
npm downloads39/mo
Monthly npm DownloadsAverage monthly package installs recorded from npm registry statistics.
51Quality signal: Good Β· 51/100How this signal is calculated β–Ύ
Server availabilityNot measured

Not scored for repo-hosted servers β€” we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20
Documentation & tools24/30
Adoption & activity4/15
Community engagement0/10

A guidance signal from public completeness & health data β€” not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 5d ago via OSV.dev Β· patternfetch-mcp (npm)

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