Binance Market Data Scraper — Spot, 24h Stats & Klines | No Auth | from $0.50/1K

Built for quant traders, algo-strategy builders, and crypto dashboards that need clean, structured Binance OHLCV data for backtesting — without a paid exchange data subscription.

No authentication required. 3,500+ trading pairs. from $0.50/1,000 tickers or $1.00/1,000 klines (Pay Per Event).

Scrape live Binance spot market data via the official public REST API. No authentication required.

What it does

Three modes:

Mode	What you get	Use case
tickers (default)	Full 24h rolling stats: price, change%, high, low, volume, trade count	Market monitoring, alerts, analysis
symbols	Lightweight last price only	Quick price snapshots for many pairs
klines	OHLCV candlestick history for any interval (1m → 1M)	Backtesting, charting, quant strategies

Supports all 3,500+ Binance spot trading pairs. Fetch one symbol, a curated list, or all pairs in a single run.

Output schema

Tickers / Symbols (modes: tickers, symbols)

Field	Type	Description
symbol	string	Trading pair (e.g. BTCUSDT)
base_asset	string	Base coin (e.g. BTC)
quote_asset	string	Quote coin (e.g. USDT)
last_price	number	Last traded price
price_change_24h	number	Absolute price change over 24h
price_change_pct_24h	number	Percentage price change over 24h
high_24h	number	24h high price
low_24h	number	24h low price
volume_24h	number	Base asset volume over 24h
quote_volume_24h	number	Quote asset volume over 24h
open_price	number	Opening price at start of 24h window
count_trades	integer	Number of trades in 24h window
parse_confidence	number	Data quality score (0.0–1.0)
warnings	array	Machine-readable warning codes

Klines (mode: klines)

Field	Type	Description
symbol	string	Trading pair
base_asset	string	Base coin
quote_asset	string	Quote coin
open_time	string	ISO 8601 UTC candle open time
close_time	string	ISO 8601 UTC candle close time
open_price	number	Opening price
high_price	number	High price
low_price	number	Low price
close_price	number	Closing price
volume	number	Base asset volume
quote_volume	number	Quote asset volume
count_trades	integer	Number of trades in candle
taker_buy_base_volume	number	Taker buy base asset volume
taker_buy_quote_volume	number	Taker buy quote asset volume
interval	string	Candle interval (1d, 1h, etc.)
parse_confidence	number	Data quality score
warnings	array	Warning codes

Input options

Option	Default	Description
mode	tickers	What to scrape: tickers, symbols, or klines
symbols	[]	Trading pairs to fetch. Empty = fetch ALL active pairs
klineSymbol	BTCUSDT	Symbol for klines mode
interval	1d	Kline interval: 1m 3m 5m 15m 30m 1h 2h 4h 6h 8h 12h 1d 3d 1w 1M
maxItems	500	Max records. 0 = no limit
quoteAssetFilter	``	(Advanced) Filter all-pairs by quote asset (e.g. USDT)
activeOnly	true	(Advanced) Skip non-TRADING status pairs
klineLimit	100	(Advanced) Candles per klines request (max 1000)

Example inputs

All USDT pairs (24h stats):

{
  "mode": "tickers",
  "symbols": [],
  "quoteAssetFilter": "USDT",
  "maxItems": 0
}

Top 3 pairs (quick price):

{
  "mode": "symbols",
  "symbols": ["BTCUSDT", "ETHUSDT", "SOLUSDT"]
}

BTC daily candlesticks (last 365 days):

{
  "mode": "klines",
  "klineSymbol": "BTCUSDT",
  "interval": "1d",
  "klineLimit": 365
}

Pricing example

Pay per result (PPE). Charged per record pushed:

Fetch	Records	Cost
3 specific pairs (tickers mode)	3	~$0.002
All USDT pairs (tickers, ~500 pairs)	500	~$0.25
100 daily BTC klines	100	~$0.10
All 3,500+ active spot pairs	~3,500	~$1.75

FAQ

Do I need a Binance account or API key? No. All endpoints used are public Binance market data — no authentication of any kind is required.

What formats can I export to? JSON, CSV, and Excel via the Apify dataset download or the REST API. Kline data maps directly to pandas DataFrame for backtesting.

Can I schedule this to run automatically? Yes. Set up a schedule in Apify Console or trigger via webhook from n8n / Make. Common use: run tickers mode every minute for a live dashboard.

What if a symbol returns empty or an error? Invalid symbols are skipped with a log warning — the actor does not crash. The warnings field in each record flags data-quality issues. Failed symbols appear in the failedDetails output key.

Notes

• No authentication required. All endpoints used are public Binance market data.
• Geo-availability: api.binance.com is accessible globally. If geo-blocked in your region, the actor will use data-api.binance.vision as a fallback automatically.
• Rate limits: Binance uses weight-based rate limiting. Single-symbol fetches use minimal weight; fetching all 3,500+ pairs at once uses higher weight but is still within public limits.
• parse_confidence: every record includes parse_confidence (0.0–1.0) so downstream pipelines can filter low-quality rows without manual inspection.
• Not affiliated with Binance. This actor uses the official Binance public REST API documented at https://binance-docs.github.io/apidocs/

Competitor comparison

Scraper	Approach	Price	Klines?	No auth?
This actor	Official Binance public API	PPE $0.50–1/1K	yes	yes
binance-price-fetcher (typical)	3rd-party lib	rental $9/mo	no	sometimes
exchange-data-scraper	HTML scraping	flat fee	no	no

Use with AI agents (MCP)

This actor is callable as a tool by AI agents (Claude Desktop, Cursor, VS Code, n8n, LangGraph, CrewAI, or any MCP-compatible client) via Apify's hosted Model Context Protocol server. An agent uses it to look up live Binance spot prices, 24h stats, or OHLCV kline history mid-conversation — e.g. "what is the current BTCUSDT price?", "show me the last 30 daily candles for ETHUSDT".

Point your MCP client at this tool:

{
  "mcpServers": {
    "apify": {
      "command": "npx",
      "args": [
        "mcp-remote",
        "https://mcp.apify.com/?tools=bovi/binance-scraper",
        "--header",
        "Authorization: Bearer <YOUR_APIFY_TOKEN>"
      ]
    }
  }
}

Minimal input an agent can send:

{ "mode": "symbols", "symbols": ["BTCUSDT", "ETHUSDT"] }

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Integrations

Built for quant traders and algo-strategy builders feeding OHLCV and 24h market stats into backtesting pipelines — the JSON/dataset output drops into the tools you already run, no glue code:

• n8n / Make / Zapier — trigger a run or pipe every new dataset item into 500+ apps (Google Sheets, Airtable, Slack, HubSpot, your database) with no code: n8n, Make, Zapier.
• Webhooks — fire your own endpoint the moment a run finishes, to push results straight into your pipeline (docs).
• MCP server — expose this actor as a tool to Claude, Cursor, or any MCP client so an AI agent can pull this data mid-conversation (guide).
• API & SDKs — fetch the dataset as JSON, CSV, or Excel through the Apify REST API or the Python / JS SDKs.

See all Apify integrations.

Usage statistics

This Actor creates a small, content-free summary at the end of each run. It is used only to monitor reliability and improve this Actor. A copy is saved as USAGE_STATS in your own Apify key-value store, so you can see the exact record created for your run.

Set disableUsageStats to true in the input to opt out. Nothing is sent then; your USAGE_STATS record only says that statistics were disabled.

Only these fields are recorded:

• schema version, Actor name and build number;
• UTC start and finish hour (not a precise timestamp);
• run duration, number of results and time to the first result, each as a coarse range;
• whether the result was empty, the end status, and an error type from a fixed list;
• memory setting and counts of charged events;
• names of the input fields you set, never their values;
• the selected option for input fields that offer a fixed list of choices (for example a sort order).

We do not collect input text, search terms, URLs, domains, usernames, email addresses, names, proxy credentials, tokens, scraped records, output items, raw error messages, stack traces, or hashes of any of those values. Records are kept for no longer than 13 months, used only as aggregated operational statistics, and never sold or shared.

Additional fields (Phase 2)

This Actor also records your Apify user ID, whether Apify marks the account as paying, the size range of list inputs, the selected country when the input offers a fixed list of countries, and one category from a fixed Actor taxonomy. We use these fields only for aggregate reliability, repeat-use and cross-Actor analysis; reports suppress any cell with fewer than five distinct users.

The same disableUsageStats: true input flag turns these fields off too. The user ID is removed after 13 months; we do not export, sell, share, or attempt to re-identify this data.

Run-outcome signals (v2)

To learn whether a run did what it was asked to do, the record also holds a few more coarse ranges and yes/no flags. None of them contains content:

• the result limit you asked for (a range, when the input has one) and what share of it was delivered;
• results delivered per input item you listed (a range);
• output quality as ranges: how fully the result fields were filled, the share of rows that look like errors, the share of duplicate rows, and how many different fields appeared. These are counted in memory while results are saved; no result content is kept;
• how the run was started (console, API, schedule, webhook, another Actor);
• how it ended: stopped by you, timed out, reached the requested limit, stopped by the charge limit, and how many times the platform moved the run;
• if this Actor reports it: how many items to process worked or failed (ranges) and one failure reason from a fixed list;
• a short code made from the names of the input fields you set, never their values.

Repeat-run fingerprint (v2)

When your Apify user ID is recorded (see above), the record also holds an 8-character one-way code made from your input (proxy settings left out) and this Actor's name. It only lets us see that the same account ran the same input again soon after an unsatisfying run; we never see the input itself. It is stored only in the database, never published, and reports use it in aggregate with the same five-user minimum. It is the one exception to the statement above that no hashes are collected, and disableUsageStats: true turns it off.