Intrinio is a serious data platform — equities, options, standardized fundamentals and estimates, delivered every way an engineering team could want them: REST, WebSocket, bulk files. Tickerbot is the layer those teams usually build next: every ticker × every signal as one computed SQL table — query it live, as of any past moment, or as a webhook subscription. Complete on its own, data included — there’s no feed to bring.
Free plan. Every ticker, every signal, real-time data, all-time history.
head to head
Intrinio delivers clean, normalized datasets — the input a data-engineering pipeline is built on. Tickerbot is the output end of that pipeline, bought instead of built: the whole market as one table where the screening, the indicator math and the history are already done.
| Intrinio | Tickerbot | |
|---|---|---|
| Market data | Normalized datasets — REST, WS, bulk | One computed table, every ticker |
| Technical indicators & signals | Compute from price & fundamental feeds | 419+ named signals, precomputed + custom |
| Stock screener | Query datasets, assemble the screen | SQL across the whole market |
| Backtest-ready history | Deep historical archives | As-of queries — any past moment |
| Stock alerts | Stream via WebSocket, compare yourself | Webhook when your condition matches |
| AI agents | AI-ready datasets in — you build the tools | Answers in — context spent on decisions |
in practice
On a raw feed, market state is something you assemble — endpoint by endpoint, symbol by symbol, indicator by indicator. On Tickerbot, the assembly has already run — everything is a read:
| The question | With a raw feed | With Tickerbot |
|---|---|---|
| Everything about one ticker | Assemble it — quote, profile, fundamentals, plus each indicator, per symbol | GET /v2/tickers/AAPL — one row, every signal |
| Every ticker in a state | Poll each symbol, compute the indicator, compare | GET /v2/signals/rsi_oversold — the current list |
| Scan the entire market | Run your universe through your own pipeline | POST /v2/scan {"q": "rsi_14 < 30 AND market_cap > 1e9"} |
Each of the three Tickerbot calls runs in three tenses: live, as of any past moment (add ?asof= — no look-ahead, no survivorship bias), or on push — the same query as a webhook that fires when the answer changes. And every Tickerbot call is a native tool for AI agents via the MCP server: hand a model computed state and its context goes to decisions; hand it raw data and the context goes to doing the math.
None of this makes a raw feed the wrong buy — the layers are different. To act on market state, you either build this layer on a feed like Intrinio’s, or buy it from Tickerbot as a table — data included; there’s no feed to bring.
the right tool
Intrinio is the right choice when the dataset itself is the requirement: options chains, standardized fundamentals your quants want to model from scratch, bulk files for a warehouse you already run, and the enterprise support to stand behind all of it — there’s a reason household-name platforms build on them. Teams like that often want Tickerbot for the other half: the already-computed market state their product or agent can query in one call.
questions
For the computed-state half of the job, yes. Intrinio delivers excellent raw datasets; the layer that turns them into running market state — screens, indicators, alerts — is yours to build. Tickerbot sells that layer finished: every ticker × 419+ computed signals as one SQL table, live, as-of any past moment, or pushed as a webhook. If you need options data or bulk fundamentals to model from scratch, that’s Intrinio’s ground.
Because every action it takes — an alert, a screen result, an order — is a condition over derived values: RSI below 30, price above the 200-day average, volume three times normal. Raw data doesn’t contain those. Something has to compute and refresh them for every symbol, continuously, and keep the history so past answers are reproducible. That’s a data pipeline, not a feature — you either build and operate it, or query one that already runs.
Naturally. Intrinio feeding the warehouse and the models your team owns; Tickerbot answering the operational questions — what matches now, what changed, what to act on — as one queryable table with webhooks.
Every call here is also a native tool call: install the MCP server and Claude, ChatGPT, Cursor, or any MCP runtime queries the market directly. Computed state is what makes that work well: hand a model raw data and its context window fills with math to do; hand it computed answers and the context goes to decisions. A scan returns the tickers matching your condition: a list, not a workload.
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.
in the wild
What people are saying.
“dude. whoah.”
“Tickerbot is insane. It turns Claude into a quant.”
“Best value for hobbyists and advanced traders alike.”
get started
Free plan. Every ticker, every signal, real-time data, all-time history.