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Chart Library vs Polygon — data versus intelligence.

Short version: Polygon is a market data API (bars, ticks, quotes, news). Chart Library is a cohort intelligence engine — a higher-order layer that sits on top of market data and answers “what did this pattern do historically?” They’re complements, not competitors.

If you’re building anything that touches stocks, you probably want both. This page covers when each fits.

What each one is

Polygon

A market data infrastructure provider. Polygon serves real-time and historical bars (1-minute, 1-second, tick), quotes, trades, corporate actions, news, options, fundamentals. Their job is moving raw data quickly and reliably. Pricing scales with symbols, history depth, and frequency. We use Polygon ourselves as the underlying data feed for Chart Library’s nightly ingest.

Chart Library

An analysis layer on top of market data. We index ~25M chart pattern embeddings across 19,000+ US equities and 10 years of minute-bar data, then expose cohort intelligence as the primitive: anchor a (symbol, date, timeframe), get the 300 most similar historical patterns, the full distribution of what they did next, and the features that separated winners from losers. See what cohort intelligence is for the full picture.

We’re a customer of a Polygon-tier data feed. Chart Library would not exist without Polygon-or-equivalent providing the underlying bars.

When to use Polygon

  • You’re building anything that needs real-time quotes or trades (charting app, alerting system, OMS).
  • You need raw historical bars at minute or tick resolution to build your own analysis layer.
  • You want options chains, fundamentals, or corporate-action data — domains Chart Library doesn’t cover.
  • You’re running a trading bot that needs execution-quality data. Chart Library’s data is end-of-day-snapshot quality and not appropriate for live execution.

When to use Chart Library

  • You’re building an AI agent that needs to reason about stocks. Cohort intelligence is the right primitive — distributions and feature attribution the agent can reason over, not raw bars it would have to analyze itself.
  • You want calibrated forward-return distributions for a setup. Polygon gives you bars; deriving a conformal-corrected probability band from those bars is the hard part. Chart Library does this for you.
  • You’re a quant or researcher doing chart pattern backtesting and want to skip building the embedding + cohort + calibration pipeline yourself.
  • You want an MCP server for finance wired into Claude or Cursor. See MCP server for finance.

When to use both

The most common pattern: Polygon for real-time + raw data, Chart Library for cohort intelligence. Concrete example — an AI trading research agent:

  • User asks: “What does NVDA’s chart look like right now?”
  • Agent calls Polygon for real-time intraday bars to render the current chart shape and price.
  • Agent calls Chart Library cohort_analyze to get the 300 historical analogs, full distribution, and feature attribution.
  • Agent synthesizes: “The current chart matches a 300-analog cohort with median 5d return -1.3%, win rate 44%. The cohort performs better in tight credit-spread environments (currently tight) but worse in low-vol regimes (currently low).”

Using only Polygon, the agent has the chart but no cohort context. Using only Chart Library, the agent has the cohort but not the live chart. Both = complete answer.

Pricing comparison (rough)

Polygon: free tier (5 requests/min, 2 years history); paid plans from $29/mo (Starter) to $499/mo (Advanced) for unlimited real-time + 10 years of data.

Chart Library: free Sandbox (200 calls/day, no auth); $29/mo Builder; $99/mo Scale. Enterprise is custom.

For a typical AI agent serving a moderate user base, you’d run Polygon Starter ($29/mo) + Chart Library Builder ($29/mo) = $58/mo total infrastructure. Both have free tiers sufficient for prototyping.

Frequently asked questions

Can Chart Library replace Polygon?
No. Chart Library doesn't expose raw bars or real-time data. The cohort_analyze response includes pre-computed forward returns from a snapshot cache, but if you need live ticks, options chains, or anything other than chart pattern intelligence, you need a market data provider — Polygon, Alpaca, or similar.
Can Polygon replace Chart Library?
Only if you build the embedding pipeline, cohort retrieval, calibration layer, and eval discipline yourself. That's a months-of-work undertaking. Most teams use Chart Library to skip the build.
Does Chart Library use Polygon under the hood?
Yes — Polygon is one of our underlying data feeds. We're a Polygon customer for the bars that feed our embedding pipeline. We're also a customer for news ingestion via the Phase 3b news features.
Why not use yfinance instead of Polygon?
yfinance has survivorship bias (delisted symbols absent), is slower, and is an unofficial scrape of Yahoo's APIs that breaks frequently. Fine for hobby projects; not appropriate for production. See chartlibrary.io/compare/chart-library-vs-yfinance.
Try it

Try cohort intelligence on top of Polygon-quality data.

Free Sandbox tier — 200 calls/day, no API key required. Real bars, real cohorts, real distributions.

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