Yahoo Finance sells you a website, scraped through libraries like yfinance. Tickerbot sells you one wide precomputed table instead.
Free plan: 10,000 calls a month, no card.
What it takes on Yahoo Finance, and the one Tickerbot call for each.
| The question | Yahoo Finance | Tickerbot |
|---|---|---|
| Did NVDA beat, and is it above its 200-day? | Ticker("NVDA").info, .history() and .earnings_dates, your own pandas for the 200-day. | GET /v2/tickers/NVDA |
| Which stocks did both? | Those calls for 20,000 tickers, rate-limited. Hours, not a step. | POST /v2/scan q=last_earnings_surprise_pct > 0 AND above_sma_200 |
| Which did, on Jan 22, 2024? | Every ticker that traded that day, delisted ones included, stored before it asked. | POST /v2/scan q=last_earnings_surprise_pct > 0 AND above_sma_200 asof=2024-01-22 |
| The moment one joins the list? | All of that again, on a loop, forever. | POST /v2/scan/subscribe q=last_earnings_surprise_pct > 0 AND above_sma_200 |
Yahoo Finance is the right tool for what it is: checking the market, and quick scripts or notebooks where an unofficial pull is perfectly fine. A great deal of good analysis starts exactly there. When a script grows into a product — users, alerts, money on the line — it needs a contract, and that’s where Tickerbot comes in: the market computed into one table, every question one call.
The stock market API designed for agents. Real-time and historical market data served as one wide precomputed table you query in SQL, where every ticker is a row and every data point, from price to 200-day average to golden cross, is a column. /v2/scan returns every row matching a SQL WHERE clause; /v2/tickers and /v2/signals are shortcuts into the same table, one row or one column.
Every US-listed equity plus rates, FX, metals and crypto, with the full schema of 427+ signals computed for each ticker. The data refreshes continuously, and all-time history sits behind every column.
Six sources. Polygon.io, under an enterprise agreement: US equity prices, bars, live snapshots, reference data, financial statements, short interest, dividends, splits, IPOs, crypto and FX history, and Benzinga analyst ratings. Alpha Vantage, under an enterprise agreement: earnings, company overviews, ETF profiles, insider transactions, news sentiment, and live crypto, FX and metals rates. The Federal Reserve Bank of New York: SOFR, EFFR and the target range. The U.S. Treasury: the daily par yield curve. The LBMA: daily gold and silver fixings. SEC EDGAR: company filings for addresses and incorporation. Every signal in the table is computed by Tickerbot from those inputs.
Other APIs serve raw feeds. That works when you have a question up front, not when your agent thinks one up every step. Tickerbot precomputes the entire market into one table, so conditions like above_sma_200 are already columns, past answers are already reproducible, and every question is one call.
An agent asks a new question every step, and on a raw feed each one is a build. On Tickerbot every question is one call: a scan returns the rows matching the condition, and every call is also a native tool call. Install the MCP server and Claude, ChatGPT, Cursor, or any MCP runtime queries the table directly.
The Free plan needs no card and carries the full data side: every ticker, every signal, real-time data, all-time history and as-of queries, at 10,000 calls a month and 60 a minute. Paid plans start at $29/mo, remove the monthly cap, and raise the rate limit; webhooks and streaming come with them. Data depth is never a tier lever: every plan sees the same table, and showing it to your own users is licensed on every plan, Free included.
What people are saying.
“dude. whoah.”
“Tickerbot is insane. It turns Claude into a quant.”
“Best value for hobbyists and advanced traders alike.”
Free plan: 10,000 calls a month, no card.