GMGN.ai Token Scraper — Meme Coins & DeFi Data

Scrape real-time trending meme-coin and DeFi token data from GMGN.ai — the leading DeFi analytics platform tracking tokens on Solana, Ethereum, Base, BSC, and Tron.

Returns 40+ fields per token including price, volume, market cap, liquidity, holder count, trading activity, and a full DeFi risk-signal suite: honeypot detection, rug ratio, sniper count, bundler rate, smart-money flow, and blue-chip ownership. No API key required. No login required. Pay per token result.

Faster alpha. Safer trades. Structured data your bots can actually use.

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What You Get — 40+ Fields Per Token

Category	Fields
Identity	address, symbol, name, chain, rank
Price	price, price_change_pct_1m/5m/1h/6h/24h, price_change_pct_period
Market	volume, market_cap, liquidity, total_supply, initial_liquidity
Trading	swaps, buys, sells
Holders	holder_count, top_10_holder_rate
Risk	is_honeypot, rug_ratio, sniper_count, bundler_rate, renounced_mint, renounced_freeze_account, bluechip_owner_percentage, smart_degen_count, bot_degen_count
Socials	twitter_username, website, telegram
Timing	open_timestamp, created_at (ISO UTC)
Quality	parse_confidence, warnings

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Why This GMGN Scraper Beats Manual Monitoring

GMGN's web UI shows you trending tokens — but you can't pipe that data into a trading bot, a risk screener, or an analytics dashboard without an API. This actor gives you exactly that: structured JSON output for every token on GMGN's trending lists, automatically, on your schedule.

• 5 chains in one run: Solana, Ethereum, Base, BSC, Tron — no separate scrapers
• 5 time windows: 1m, 5m, 1h, 6h, 24h — catch both micro-momentum and daily trends
• Risk signals baked in: honeypot + rug ratio + sniper count in every record — no manual filtering
• parse_confidence on every record: machine-readable quality signal so your pipeline knows when the source has changed

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How to Use

Trending mode (default)

{
  "mode": "trending",
  "chains": ["sol", "eth"],
  "periods": ["1h", "24h"],
  "orderby": "swaps",
  "filters": ["not_honeypot"]
}

• chains: sol, eth, base, bsc, tron
• periods: 1m, 5m, 1h, 6h, 24h
• orderby: swaps, volume, marketcap, holder_count, smartmoney, liquidity, open_timestamp
• filters: optional safety pre-filters — not_honeypot, renounced, verified

Each chain × period combination returns up to 100 tokens.

Token detail mode

{
  "mode": "token_detail",
  "chains": ["sol"],
  "tokenAddresses": [
    "So11111111111111111111111111111111111111112",
    "EPjFWdd5AufqSSqeM2qN1xzybapC8G4wEGGkZwyTDt1v"
  ]
}

Fetches metadata (decimals, circulating supply, pool address, creation time) for specific token addresses.

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Use Cases

Trading bot alpha feed

Pull 1m and 5m trending tokens sorted by swaps to detect early momentum before price moves. Filter is_honeypot=false server-side and feed directly into your entry logic.

DeFi risk screening

Before buying any token, verify rug_ratio, sniper_count, and bundler_rate. Tokens with renounced_mint=true and bluechip_owner_percentage > 0.05 signal safer projects.

Cross-chain market analytics

Compare trending volume across Solana vs Ethereum vs Base simultaneously. Identify which chains show early capital rotation.

AI agent data layer

Works as a structured data source for AI agents via the Apify MCP server. Your LLM agent can pull fresh token data on demand without custom API integration.

Smart-money tracking

Filter by smart_degen_count > 0 to find tokens attracting attention from GMGN's tracked smart wallets before they trend in mainstream feeds.

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Pricing

$2.00 per 1,000 token results (Pay Per Event — token-result).

Run scope	Tokens	Cost
Single chain × single period (e.g. sol/1h)	~100	$0.20
2 chains × 2 periods	~400	$0.80
Full sweep (5 chains × 5 periods)	~2,500	$5.00

You only pay for tokens successfully returned. Failed fetches are not charged.

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Technical Notes

Access handling

Uses lightweight HTTP requests that pass Cloudflare's checks without a browser or any API key (verified live 2026-06-04).

Parse confidence

Every record includes parse_confidence (0.0–1.0). Values below 0.8 indicate the API response structure may have changed — your downstream pipeline can alert on this without manual checks.

Proxy

Default: Apify Residential (buyer-paid). Datacenter IPs may receive higher Cloudflare bot scores — residential is the safe default for cloud runs.

No API key required

GMGN's public trending endpoints are accessible without authentication. This actor requires no GMGN account, no API subscription.

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Not affiliated with GMGN.ai. Data is retrieved from publicly accessible GMGN.ai endpoints.

Integrations

Built for DeFi traders and on-chain analysts feeding meme-coin risk signals and smart-money flows into trading bots — 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.

What it does

GMGN.ai Token Scraper — Meme Coins & DeFi Data is a data-collection tool for the ai, marketing, and developer tools category. The inputs let you set the scope and preferences for a run, while the results provide organized records that are easier to review and use.

Input

Provide the values that define the scope and preferences for the run. Review each option before starting so the resulting dataset matches the information you want to analyze or reuse.

Name	Type	Description	Default
chains	array	Blockchain(s) to scrape. Supported: sol (Solana), eth (Ethereum), base (Base), bsc (BNB Chain), tron (Tron). Default: ['sol']. Multiple chains produce independent result sets.	["sol"]
filters	array	Optional GMGN API filters to apply. Common values: not_honeypot, renounced, verified. Leave empty for unfiltered results (includes risky tokens).	—
includeTokenDetail	boolean	When enabled in trending mode, makes an additional /api/v1/token_info request per token to add decimals, circulating_supply, biggest_pool_address fields. Slower and more requests, but richer data.	false
maxResults	integer	Maximum total records to push across all chains+periods. 0 = no limit (returns all). Each chain×period combination yields up to 100 tokens.	0
mode	string	trending — fetch top 100 tokens from GMGN rank/swaps (default). token_detail — fetch metadata for specific token addresses you supply.	"trending"
orderby	string	Field to sort trending results by. swaps = most active trading. volume = highest USD volume. marketcap = largest market cap. holder_count = most holders. smartmoney = smart-money trader flow. liquidity = most liquid. open_timestamp = newest tokens.	"swaps"
periods	array	Time window(s) for trending mode. Options: 1m, 5m, 1h, 6h, 24h. Each period returns up to 100 tokens sorted by the orderby field. Multiple periods = independent result sets.	["1h"]
proxyConfiguration	object	Apify proxy settings. Default residential proxy recommended for reliable access. The actor uses curl_cffi Chrome impersonation to match a real Chrome TLS profile. Datacenter IPs may be less reliable; residential increases reliability.	{"useApifyProxy":true,"apifyProxyGroups":["RESIDENTIAL"]}
tokenAddresses	array	List of token contract addresses to look up. Required when mode=token_detail. Example for Solana: ['So11111111111111111111111111111111111111112']	—

Output

A successful run produces a dataset of structured items collected according to your inputs. You can review the records, use them in analysis, or pass them to another part of your workflow. The exact fields depend on the source data and the options selected for the run.

Usage

1. Open the actor page.
2. Fill in the input values and review the configuration.
3. Run the actor and wait for the collection to finish.
4. Download the results from the dataset and use the records in your preferred workflow.

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.