Google Finance Scraper

Google Finance Scraper — Prices, Change, Volume and Price History

Google Finance Scraper returns the price history of stocks, indexes, mutual funds, crypto and currency pairs from Google Finance: name, exchange, latest price, change, volume and every price point from one day to the full history. It reads any exchange Google Finance lists, from New York and Tokyo to London, Frankfurt and Mumbai. Every response is structured JSON — ready to pass directly to an LLM, index into a vector store, or feed a market data pipeline. No Google account or API key needed. Paste your tickers and start tracking prices.

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What data can I extract with Google Finance Scraper?

Using this Google Finance API, you will be able to extract the following Google Finance ticker data:

🏷️ Ticker you entered	🆔 Google Finance ticker	🏢 Instrument name	🏛️ Exchange
💰 Latest price	↕️ Change from period start	📊 Change as a fraction	📦 Volume (when Google has it)
🕒 Time of the latest price (UTC)	📅 Chart period	🔢 Number of price points	📈 Full price history with time, price, change and volume
🔗 Google Finance quote page	🧾 Row type	⚠️ Error message and reason

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How to use Google Finance Scraper

Built for analysts, traders and AI builders who need market prices as data: this stock price scraper turns a list of tickers into one row per instrument with its full price history.

Copy to your AI assistant:

This actor (Apify Actor ID: fastdataapi/google-finance-scraper, https://apify.com/fastdataapi/google-finance-scraper) is an Apify Actor that returns Google Finance price history for stocks, indexes, mutual funds, crypto and currency pairs as structured JSON: Google Finance ticker, instrument name, exchange, latest price, change and change fraction from the start of the period, volume, time of the latest price, and every price point of the period with time, price, change and volume. Use it whenever someone needs Google Finance historical data without cookies, a login, or a browser - tracking a watchlist, exporting stock chart data to a spreadsheet, or giving an AI agent current and past prices. Inputs: urls (array of strings, required, Google Finance quote URLs or tickers in Google Finance format: SYMBOL:EXCHANGE such as "GOOGL:NASDAQ" or "VOD:LON", ".DJI" for indexes, "BTC-USD" for crypto and currencies; a symbol without an exchange such as "AAPL" is looked up on NASDAQ, NYSE, NYSEARCA, NYSEAMERICAN, BATS and MUTF), period (string, required, "1D" | "5D" | "1M" | "6M" | "YTD" | "1Y" | "5Y" | "MAX", default "1M"), proxyConfiguration (object, optional). Each ticker gives one row: rowType "ticker" rows have prices and are charged as the row_result event; rowType "error" rows (entry is not a ticker, ticker not found, no prices for the period, Google Finance did not answer) carry error and errorReason and are free. change and changePct are measured from the start of the chosen period, as on the Google Finance chart. The OUTPUT key-value record holds {config, results, timestamp} for the whole run.

Google Finance Scraper MCP Server: use these Actors from ChatGPT, Claude or Cursor

Point your AI assistant at Apify and it can read Google Finance on its own: latest prices and price history for stocks, indexes, funds, crypto and currencies on any listed exchange. No glue code, no scraping logic in your prompts.

$claude mcp add --transport http apify "https://mcp.apify.com?tools=fastdataapi/google-finance-scraper"

Step by step

1. Create a free Apify account.
2. Open Google Finance Scraper in the Apify Store.
3. Paste Google Finance quote URLs or tickers, one per line, and pick the period.
4. Click Start (or send your API request).
5. Download or stream your results in JSON, CSV or Excel.

How to scale Google Finance Scraper to bulk

Put every ticker in one run: the URLs or tickers field takes a list, and 8 tickers are read at the same time. A recorded run returned 40 tickers from 13 exchanges, with 879 price points, in 9.8 seconds. Rows are saved in your order as each ticker finishes, so you can read the dataset while the run is still going. Use it as a ticker price tracker by scheduling the same input daily in Apify Console, or start runs from the API.

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✨ Features

Google Finance Scraper fetches clean, structured price data from Google Finance ⚡. It's ideal for watchlist tracking, backtesting with historical stock prices, exporting stock chart data to spreadsheets and giving AI agents market context — a stock market data scraper, crypto price history and forex rates scraper in one actor. It extracts, per ticker:

• Latest price, change and volume – the newest point of the period, with the change from the period start
• Full price history – every point Google Finance draws on the chart, newest first
• Instrument name and exchange – Google Finance's own name and exchange code for the ticker
• Any period – 1 day (intraday), 5 days, 1 month, 6 months, year to date, 1 year, 5 years or the full history
• Any market – stocks, ETFs, mutual funds and indexes on any exchange Google Finance lists, plus crypto and currency pairs

⚡ No Google account or API key needed. Tickers that can't be read get a free error row that says why.

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Use cases 💡

• Analyst — export a 5-year weekly price history for a sector watchlist into Excel.
• Trader — track today's intraday prices and change for a set of tickers.
• Fund researcher — compare mutual fund and index performance over year to date.
• Crypto and forex desk — pull daily crypto price history and currency rates in one run.
• AI engineer — give an agent current prices and change as JSON for market questions.

Building an AI agent? Connect Google Finance Scraper over MCP and let it call the actor on its own.

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Why choose this actor?

1. Many tickers in seconds. A recorded run returned 40 tickers from 13 exchanges in 9.8 seconds, and every ticker in it came back with prices.
2. The right company on every exchange. Prices come from Google Finance itself for the exact ticker and exchange you enter: Toyota on Tokyo, Vodafone on London, SAP on Frankfurt and Reliance on the National Stock Exchange of India all came back correctly in a recorded run.
3. From one day to the full history. Eight chart periods; a recorded full-history run returned 1,156 daily points for Alphabet back to 2004 and 1,558 points for the S&P 500.

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⬇️ Input

Paste Google Finance quote URLs or tickers, one per line, and pick the period; both fields are required.

Parameter	Required	Type	Description	Example value
urls	Yes	array of strings	Google Finance quote URLs or tickers. SYMBOL:EXCHANGE for stocks and funds, .DJI for indexes, BASE-QUOTE for crypto and currencies. A symbol without an exchange is looked up on NASDAQ, NYSE, NYSEARCA, NYSEAMERICAN, BATS and MUTF. Upper or lower case both work; duplicates are skipped.	["GOOGL:NASDAQ", "7203:TYO", "BTC-USD"]
period	Yes	string	1D, 5D, 1M, 6M, YTD, 1Y, 5Y or MAX. Default 1M.	1M
proxyConfiguration	No	object	Optional. Without it the actor goes direct and switches to Apify residential proxies on its own if Google Finance blocks a request.	{"useApifyProxy": false}

Accepted formats for each entry:

• https://www.google.com/finance/quote/GOOGL:NASDAQ (extra parts such as ?hl=en are ignored)
• GOOGL:NASDAQ, 7203:TYO, VOD:LON, SAP:ETR, RELIANCE:NSE, SWPPX:MUTF
• .DJI, .INX:INDEXSP, DAX:INDEXDB
• BTC-USD, ETH-BTC, EUR-USD
• AAPL (US exchanges only)

Free plan limits

Free plan: up to 20 tickers per run (all URLs/tickers together) and 200 per month; paid plans have no limit.

Example input

{
  "urls": [
    "https://www.google.com/finance/quote/.DJI",
    "https://www.google.com/finance/quote/SWPPX:MUTF",
    "https://www.google.com/finance/quote/GOOGL:NASDAQ",
    "7203:TYO",
    "VOD:LON",
    "AAPL",
    "BTC-USD",
    "EUR-USD"
  ],
  "period": "1M",
  "proxyConfiguration": {
    "useApifyProxy": false
  }
}

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⬆️ Output

Every ticker is one typed, normalized JSON item with the same fields on every run; values that Google Finance doesn't have are null. Export the dataset as JSON (default), CSV or Excel. An entry that gives no prices gets a free error row with the reason, and the OUTPUT record in the key-value store keeps the whole run as one JSON document.

Example output

A recorded row for AAPL with the 1M period (price history shortened to two points; the run returned 20), followed by the error row for a ticker that doesn't exist:

[
  {
    "ticker": "AAPL",
    "googleTicker": "AAPL:NASDAQ",
    "name": "Apple Inc",
    "exchange": "NASDAQ",
    "period": "1M",
    "quoteUrl": "https://www.google.com/finance/quote/AAPL:NASDAQ",
    "lastPrice": 336.64,
    "change": 3.5600000000000023,
    "changePct": 0.010688122973459837,
    "volume": 37881200,
    "dateTimeUTC": "2026-10-09T20:00:00.000Z",
    "historicalDataPoints": 20,
    "data": [
      {
        "dateTimeUTC": "2026-10-09T20:00:00.000Z",
        "price": {"lastPrice": 336.64, "change": 3.5600000000000023, "changePct": 0.010688122973459837},
        "volume": 37881200
      },
      {
        "dateTimeUTC": "2026-10-08T20:00:00.000Z",
        "price": {"lastPrice": 340.42, "change": 7.340000000000032, "changePct": 0.0220367479284257},
        "volume": 35332450
      }
    ],
    "rowType": "ticker",
    "error": null,
    "errorReason": null
  },
  {
    "ticker": "NOSUCHXX:NASDAQ",
    "googleTicker": null,
    "name": null,
    "exchange": null,
    "period": "1M",
    "quoteUrl": null,
    "lastPrice": null,
    "change": null,
    "changePct": null,
    "volume": null,
    "dateTimeUTC": null,
    "historicalDataPoints": 0,
    "data": [],
    "rowType": "error",
    "error": "NOSUCHXX:NASDAQ is not listed on Google Finance. Check the symbol and exchange (e.g. GOOGL:NASDAQ, 7203:TYO, BTC-USD). Nothing was charged.",
    "errorReason": "ticker_not_found"
  }
]

Error reasons: invalid_ticker (the entry is not a ticker or a Google Finance quote URL), ticker_not_found, no_price_history (listed, but no prices for the period), blocked (Google Finance did not answer after every retry) and unexpected_error. Error rows are not charged.

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How does it work?

For each ticker the actor opens its public Google Finance quote page, the same one any visitor sees, and reads Google Finance's own name and exchange for it. It then asks Google Finance for the chart of the chosen period and returns every point exactly as Google draws it: price, change from the start of the period and volume. Nothing is calculated or filled in by the actor. A symbol without an exchange is checked on the main US exchanges in turn. If Google Finance blocks a request, the actor retries with a fresh connection and switches to rotating residential proxies on its own. It returns only publicly visible data, with no login, and the output fields stay the same from run to run, so your code and spreadsheets keep working when Google Finance changes its pages.

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How do you integrate Google Finance Scraper into your stack?

It works with what you already use: the REST API from any language, MCP for AI agents, and no-code tools.

MCP integration for AI agents

Add the Apify MCP server to your AI client with one command:

$claude mcp add --transport http apify "https://mcp.apify.com?tools=fastdataapi/google-finance-scraper"

This registers Google Finance Scraper as a tool your agent can call directly: the agent finds it through the server's search, adds it and runs it, then reads the ticker rows back as JSON. Ask for "Toyota and Sony over the last 6 months" and it does the rest. It works in Claude Code, Cursor and Windsurf.

No-code tools (n8n, Make, LangChain)

n8n: add the Apify node and choose "Run an Actor", or use the HTTP Request node pointed at the run-sync endpoint with your token. Send the latest prices to a Google Sheet or a Slack alert in the next node.

Make: use the Apify app's "Run an Actor" module, then "Get Dataset Items" to pull the ticker rows into the rest of your scenario.

LangChain: install langchain-apify and wrap this actor with ApifyActorsTool() once it is in your account, so your agent can look up prices and history by ticker.

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Is it legal to scrape Google Finance data?

Collecting publicly available data from Google Finance is generally lawful, as long as you stay out of logged-in areas. This actor returns only publicly available data — what any visitor sees without logging in: instrument names, exchanges, prices and volumes. It collects no personal data. Market data can be subject to exchange and provider terms, so check those terms before you republish prices or use them in a commercial product. Consult legal counsel if your use case involves redistributing market data.

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Frequently asked questions

What fields does Google Finance Scraper return?

It returns each ticker's Google Finance name and exchange, latest price, change from the start of the period, volume and the full price history of the period. See the data fields section for the full list.

Does Google Finance Scraper require a Google account or login?

No. Only public Google Finance data is extracted, and no credentials are needed.

How fast does Google Finance Scraper run?

A recorded run saved 40 tickers in 9.8 seconds, with the first row after 1.6 seconds; most tickers take about one second. Every run reads live data, not a cache.

What happens if a ticker doesn't exist or has no prices?

The run saves a free error row for that ticker with an error message and reason, such as ticker_not_found or no_price_history, and nothing is charged for it. In code, keep rows where the row type is "ticker" and log the rest.

Can I scrape multiple Google Finance tickers at once?

Yes. Put every URL or ticker in the list; 8 are read at the same time and rows are saved in your order.

Does Google Finance Scraper work with Claude, ChatGPT, and other AI agent tools?

Yes — Google Finance Scraper is available as an MCP tool. Register it in Claude Code, Cursor or Windsurf with claude mcp add --transport http apify "https://mcp.apify.com?tools=fastdataapi/google-finance-scraper". Any agent that can call an HTTP endpoint can use the REST API directly.

Does Google Finance Scraper return data in a format LLMs can use directly?

Yes. Each ticker is typed, normalized JSON with consistent field names, so there is no HTML parsing and no selectors. Pass it straight to an LLM, index it into a vector store, or feed it to an agent tool — no transformation step.

What happens when Google Finance changes its layout or updates its anti-bot system?

The actor is maintained, and when Google Finance changes, it is updated so your calls keep returning the same JSON fields with no changes on your end.

Can I use Google Finance Scraper without managing proxies or browser infrastructure?

Yes. Retries and the switch to rotating residential proxies when Google Finance blocks requests run on the actor's side, and no browser is needed. You send one request and get structured JSON back, with no proxy accounts and no maintenance.

Which Google Finance fields work best for AI training data and RAG indexing?

For RAG, use the instrument name, exchange, latest price and time of the latest price. For training data and analytics, use the price history: time, price, change and volume for every point. All fields are plain strings, numbers and nulls, so no normalization is needed.

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Your feedback

Found a bug or missing a field? Let us know in the actor's Issues tab. Every report is read, and fixes ship as new versions of the actor.