// stock market api

The first stock market API built for agents.

Pre-computed, categorical facts instead of raw OHLCV. Your agent gets answers, not data to process.

// the difference

Raw data vs. categorical facts.

Traditional stock market APIs return rows of OHLCV data. Your agent then needs to compute indicators, determine trend direction, classify momentum state, and figure out what it all means. TickerDB does that computation for you and returns the answer directly.

traditional stock api

json 50 rows of OHLCV

// 500+ tokens of raw OHLCV data
// Your agent has to figure out
// what any of this means

[
  {
    "date": "2026-03-28",
    "open": 213.50,
    "high": 216.82,
    "low": 212.10,
    "close": 215.74,
    "volume": 48293100
  },
  {
    "date": "2026-03-27",
    "open": 210.25,
    "high": 214.10,
    "low": 209.80,
    "close": 213.50,
    "volume": 52107300
  },
  // ... 47 more rows
]

tickerdb

json one GET request

// Pre-computed facts your agent
// already understands

{
  "ticker": "AAPL",
  "trend": {
    "direction": "uptrend",
    "duration_days": 12,
    "volume_confirmation": "confirmed"
  },
  "momentum": {
    "rsi_zone": "neutral_high",
    "macd_state": "expanding_positive"
  },
  "volatility": {
    "regime": "normal",
    "squeeze_active": false
  },
  "support_level": {
    "distance_band": "moderate",
    "status": "intact"
  }
}

// how we compare

Not another raw data provider.

Most stock market APIs return the same thing: OHLCV bars and maybe some indicators. TickerDB does the computation and returns the conclusions.

TickerDB Traditional APIs

Response format Categorical facts Raw OHLCV / numbers

Indicator computation Pre-computed You build it

LLM compatibility Native vocabulary Needs prompt engineering

Context window usage Compact Token-heavy

Infrastructure needed None Sync, cron, pipelines

Historical pattern analysis Built-in summary event mode Build your own

vs Alpha Vantage → vs Polygon.io → vs Twelve Data → vs Massive → vs EODHD → vs FMP →

// strongest use cases

Where this API is strongest.

TickerDB is best when your agent needs a fast market answer, a historical setup check, or a portfolio diff. These workflows benefit most from categorical data instead of raw bars.

Watchlist monitoring

Detect field-level changes across saved tickers with one call, then alert users or trigger follow-up analysis only when something meaningful moved.

Market scanning

Find oversold names, rare setups, strong trends, or valuation mismatches across the whole market with structured filters instead of custom indicator code.

Historical precedent

Use summary event mode to ask when a condition last happened, how rare it is, and what the usual aftermath looked like.

AI research copilots

Generate ticker briefings, trade notes, and portfolio commentary with compact market context that fits neatly into model context windows.

// how it works

Plain HTTP. Bearer token. JSON back.

Standard GET requests. No SDK required. Works with any language, any framework, any agent runtime.

terminal

$ curl https://api.tickerdb.com/v1/summary/AAPL \
  -H "Authorization: Bearer tapi_your_key"

GET /v1/summary/{ticker}

Full factual snapshot: trend, momentum, volatility, volume, support/resistance, and fundamentals for any ticker.

GET /v1/watchlist

Portfolio monitoring. Returns current state for all saved tickers in a single call.

GET /v1/watchlist/changes

Day-over-day state changes for your saved tickers. Monitor a portfolio with one call.

GET /v1/search

Multi-field scans across all assets. Find oversold names, rare conditions, strong trends, or valuation setups in a single request.

POST /v1/webhooks

Push notifications when state changes fire. Get alerted when tickers cross important thresholds.

full API reference →

// historical analysis

Every band transition. Every aftermath.

The summary endpoint's event mode returns every historical instance of a state transition for any ticker and field, with aftermath data showing what happened next. Your agent gets pattern analysis without touching a single price bar.

json GET /v1/summary/SVC?field=rsi_zone&band=deep_oversold

{
  "ticker": "SVC",
  "field": "rsi_zone",
  "total_occurrences": 3,
  "events": [
    {
      "date": "2026-03-31",
      "band": "deep_oversold",
      "duration_days": 2,
      "aftermath": {
        "5d": "slight_gain"
      }
    },
    "...": // more events
  ]
}

Aftermath data

Every event includes what happened 5, 10, and 20 days later. Your agent sees historical outcomes directly without computing returns from raw prices.

Cross-asset correlation

Events include cross-asset context so your agent can see whether similar transitions happened across related tickers at the same time.

Condition rarity

Every summary includes how rare the current condition is historically for that specific asset. An "extremely_rare" oversold reading means something different than a routine dip.

10,800+ US stocks

1,500+ ETFs

200+ Crypto

Daily Refresh after close

// works everywhere