Dexscreener Scraper — DEX Pairs, Token Prices & Trending | All Chains | from $1.50/1K

For DeFi traders, crypto market makers, and on-chain intelligence platforms that need structured pair data across all major blockchains — including real-time token prices, liquidity, FDV, and trending social metadata.

No auth required. All chains — Ethereum, Solana, BSC, Polygon, Arbitrum, Base and 50+ more. $1.50/1,000 pair records · $3.00/1,000 token profiles (Pay Per Event).

Scrape live DEX (decentralized exchange) trading pair data from Dexscreener via the official public API. Search by token name or symbol, look up specific pairs by chain and address, fetch all pairs for a token, or browse the latest trending token profiles. No API key or authentication required.

What data you get

Each DEX pair record includes:

Field	Description
chain_id	Blockchain (ethereum, solana, bsc, polygon, arbitrum, base, …)
dex_id	DEX name (uniswap, raydium, pancakeswap, …)
pair_address	Pair contract address
base_token_symbol	Base token ticker (e.g. PEPE, BTC)
base_token_name	Base token full name
base_token_address	Base token contract address
quote_token_symbol	Quote token ticker (e.g. WETH, USDT)
quote_token_name	Quote token full name
quote_token_address	Quote token contract address
price_usd	Current price in USD
price_native	Current price in quote token units
liquidity_usd	Total liquidity in USD
volume_24h	24-hour trading volume in USD
price_change_24h	% price change over the last 24 hours
fdv	Fully diluted valuation in USD
market_cap	Market cap in USD
pair_created_at	ISO 8601 date when the pair was created on-chain
url	Canonical Dexscreener URL
parse_confidence	Data quality score 0.0–1.0
warnings	Machine-readable warning codes

For profiles mode, icon_url, description, website_url, and twitter_url are also populated.

Modes

• search — Find pairs by token name or symbol. Each query returns up to 30 matching pairs across all chains and DEXes.
• pairs — Fetch specific pairs by chain/pairAddress. Up to 30 per chain in one call.
• tokens — Fetch all pairs for a token contract address (up to 30 per token).
• profiles — Fetch the latest trending token profiles with descriptions and social links.

Use cases

• Crypto market monitoring dashboards
• DeFi arbitrage and liquidity analysis
• Token launch tracking and research
• On-chain data enrichment pipelines
• Meme coin discovery and trend analysis

Pricing example

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

Fetch	Records	Cost
Search "PEPE" (top 30 pairs)	30	~$0.045
10 specific pair addresses	10	~$0.015
All pairs for 1 token address	up to 30	~$0.045
Latest trending profiles (top ~30)	~30	~$0.09
1,000 search results	1,000	~$1.50

No proxy costs — Dexscreener API is fully public, zero infrastructure cost to you.

FAQ

Do I need a Dexscreener account or API key? No. The Dexscreener public API requires no authentication of any kind.

What formats can I export to? JSON, CSV, and Excel via the Apify dataset or REST API. The flat schema maps directly to pandas or Google Sheets.

Can I schedule this to run automatically? Yes. Schedule in Apify Console (e.g. every 5 minutes) or trigger via n8n / Make webhook to build a live on-chain monitoring feed.

What if a query returns empty or a token address is invalid? Empty queries are skipped with a log warning. Invalid or unlisted token addresses return zero pairs — the actor logs and continues, no crash. Check failedDetails in the output for any failed lookups.

Trust signal

Every record includes parse_confidence (1.0 = all expected fields present, below 1.0 = missing/unexpected data). Use this for downstream quality filtering without manual inspection.

Competitor comparison

Scraper	Chains	Price model	Social data?	parse_confidence?
This actor	50+ chains	PPE $1.50–3/1K	yes (profiles mode)	yes
dextools-scraper (DOM)	Ethereum, BSC	rental	no	no
moralis-price-api (3rd-party)	5 chains	$49/mo	no	no
dexscreener-unofficial	Some chains	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 on-chain token prices, liquidity, and trending DeFi pairs mid-conversation — e.g. "what is the current price of PEPE on Ethereum?", "show me trending tokens with liquidity > $100K".

Point your MCP client at this tool:

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

Minimal input an agent can send:

{ "mode": "search", "queries": ["PEPE"], "maxItems": 10 }

Notes

• Official Dexscreener public API — no authentication required.
• Rate limits are generous; the actor adds small delays between batch calls.
• This actor is not affiliated with or endorsed by Dexscreener.

Also in this finance family

• CoinGecko Scraper — live crypto prices, market caps, all coins
• Binance Scraper — spot prices + OHLCV klines for 3,500+ pairs
• Yahoo Finance Scraper — stocks, ETFs, crypto, indices, forex
• DefiLlama Scraper — DeFi protocol TVL + yield pool APY
• ECB Exchange Rates Scraper — historical FX rates back to 1999

Integrations

Built for DeFi traders and on-chain intelligence platforms tracking live DEX pair prices, liquidity, and trending tokens — 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.

More scrapers from our toolkit

Building a data pipeline? These actors pair well with this one — each runs on your own Apify account with the same pay-per-result pricing, no subscription:

• Coingecko Scraper
• Credential Breach Checker
• Github Scraper
• Hacker News Scraper

Chain any of them together from the Integrations tab (the Run succeeded trigger) to build a multi-step workflow — one actor's output feeds the next.

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.