# Trending Token Scanner - Sustained vs Spike Classifier (`centorprat/trending-token-scanner`) Actor

Scans trending DEX pools across chains (keyless) and classifies each move - sustained uptrend vs a thin spike likely to retrace - using multi-timeframe volume acceleration, buy pressure and liquidity, with a sustainabilityScore and dumpRisk flag. Signals, not predictions. Read-only, agent-callable.

- **URL**: https://apify.com/centorprat/trending-token-scanner.md
- **Developed by:** [Centor Prat](https://apify.com/centorprat) (community)
- **Categories:** Developer tools
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $17.00 / 1,000 scan runs

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## Trending Token Scanner — Sustained vs Spike Classifier

Not just *what's* trending — *which trends are real*. The scanner pulls the trending pools across chains (keyless) and classifies each move as a **sustained uptrend** vs a thin **spike** likely to retrace, using the multi-timeframe signals a person can't weigh at scale: price across 1h/6h/24h, **volume acceleration** (is it speeding up or dying?), buy/sell pressure, unique buyers, and liquidity depth. Each gets a **sustainabilityScore** and a **dumpRisk** flag. Read-only, keyless, agent-callable.

> Observable **signals**, not a price prediction and not financial advice. "sustained-uptrend" is not a guarantee; crypto is high risk — verify everything.

### What it does

- Scans **trending** pools on Ethereum, BSC, Base, Solana, Polygon, Arbitrum, Avalanche (keyless GeckoTerminal).
- Classifies each into: **sustained-uptrend** · **accumulating** · **spiking** · **fading** · **distribution** · **mixed**.
- Computes a **sustainabilityScore (0–100)** (liquidity depth + healthy-not-parabolic trend + volume not decelerating + buy pressure + buyers) and a **dumpRisk** flag (thin/decelerating/sell-heavy spikes).

| Field | Meaning |
|---|---|
| `classification` | the move-quality label |
| `sustainabilityScore` | 0–100, how "backed" the move looks |
| `dumpRisk` | thin/decelerating/sell-heavy spike warning |
| `priceChangeH1/H6/H24Pct` | trend across timeframes |
| `volumeAcceleration` | h1 rate ÷ h6 rate (>1 = speeding up) |
| `buyPressureH1`, `uniqueBuyersH1`, `liquidityUsd` | flow + depth |
| `reasons[]` | why it classified that way |

### Why not just ask an AI agent / why not a "trending list"?

A plain trending list tells you something moved. It **can't** tell you a token up 400% on the day is actually down 50% in the last 6 hours on dead volume (a dump in progress) vs one grinding steadily higher on rising volume and buyers. This weighs those multi-timeframe deltas deterministically and labels the **quality** of each move — the part that matters.

### Input

| Field | Type | Default | Description |
|---|---|---|---|
| `networks` | array | ethereum, bsc, base, solana | Chains to scan. |
| `minLiquidityUsd` | integer | 20000 | Ignore thinner trending pools. |
| `maxCandidates` | integer | 25 | Top rows to return. |
| `webhookUrl` | string | | POST the ranked scan here. |

**Example input**

```json
{ "networks": ["ethereum", "bsc", "base", "solana"], "minLiquidityUsd": 20000 }
```

### Output

One row per trending pool. **Example** (real run, trimmed):

```json
{
  "name": "CATE / SOL",
  "network": "solana",
  "classification": "sustained-uptrend",
  "sustainabilityScore": 71,
  "dumpRisk": false,
  "liquidityUsd": 3103083.52,
  "priceChangeH1Pct": 7, "priceChangeH6Pct": 17, "priceChangeH24Pct": 20,
  "volumeAcceleration": 2.08,
  "reasons": ["up across 1h (7%) and 24h (20%)", "volume accelerating (2.1x the 6h rate)"]
}
```

…while a token up +402% on the day but −50% over the last 6h on dead volume classifies as **fading** — exactly the retrace this is built to catch.

### Use cases

- **Separate real moves from pumps** — act on sustained trends, skip the dump-risk spikes.
- **A standing "what's actually moving" feed** — schedule + webhook.
- **AI trading/research agents** — a classified, scored trending list to reason over.

### Ready-made tasks

- [Trending Crypto Tokens Across Chains](https://apify.com/centorprat/trending-token-scanner/examples/trending-crypto-all-chains)

### For AI agents / MCP

```
https://mcp.apify.com/?tools=actors,docs,centorprat/trending-token-scanner
```

Loads as `centorprat--trending-token-scanner`. Claude Code:

```
claude mcp add apify -- npx -y @apify/actors-mcp-server --actors centorprat/trending-token-scanner
```

### FAQ

**How is this different from a new-token scanner?** That finds *brand-new* launches; this reads tokens that are *already trending* and judges whether the move is sustained or likely to retrace.

**Which chains?** Ethereum, BSC, Base, Solana, Polygon, Arbitrum, Avalanche.

**Does it need a key?** No — keyless public DEX data.

**Does a high sustainabilityScore mean "buy"?** No. It means the move currently has more of the hallmarks of a backed trend than a thin spike. It's a signal to review, not advice.

**How fast / how much?** A couple of seconds per scan. Pay-per-event: a base per scan + a small premium per candidate returned.

### Data & attribution

Public DEX market data via the keyless GeckoTerminal API. No keys, no personal data. Signals, not financial advice.

### Related actors

- [New Token Momentum Scanner](https://apify.com/centorprat/new-token-momentum-scanner)
- [DEX Token Market Snapshot](https://apify.com/centorprat/dex-token-market-snapshot)
- [Token Price & Liquidity Alert Monitor](https://apify.com/centorprat/token-price-liquidity-alert-monitor)
- [Token Honeypot & Rug Pull Safety Check](https://apify.com/centorprat/token-honeypot-rugpull-check)

# Actor input Schema

## `networks` (type: `array`):

Chains to scan for trending pools. Options: ethereum, bsc, base, solana, polygon, arbitrum, avalanche.

## `minLiquidityUsd` (type: `integer`):

Ignore trending pools thinner than this (trending + thin = pump-risk).

## `maxCandidates` (type: `integer`):

How many top candidates to return.

## `webhookUrl` (type: `string`):

If set, the ranked scan is POSTed here as JSON when the run completes.

## Actor input object example

```json
{
  "networks": [
    "ethereum",
    "bsc",
    "base",
    "solana"
  ],
  "minLiquidityUsd": 20000,
  "maxCandidates": 25
}
```

# Actor output Schema

## `candidates` (type: `string`):

One row per trending pool: chain/dex/name/token, liquidity, FDV, multi-timeframe volume + price change, volume acceleration, buy pressure, unique buyers, a classification (sustained-uptrend / accumulating / spiking / fading / distribution / mixed), a sustainabilityScore and a dumpRisk flag. Signals, not predictions.

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "networks": [
        "ethereum",
        "bsc",
        "base",
        "solana"
    ],
    "minLiquidityUsd": 20000,
    "maxCandidates": 25
};

// Run the Actor and wait for it to finish
const run = await client.actor("centorprat/trending-token-scanner").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "networks": [
        "ethereum",
        "bsc",
        "base",
        "solana",
    ],
    "minLiquidityUsd": 20000,
    "maxCandidates": 25,
}

# Run the Actor and wait for it to finish
run = client.actor("centorprat/trending-token-scanner").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "networks": [
    "ethereum",
    "bsc",
    "base",
    "solana"
  ],
  "minLiquidityUsd": 20000,
  "maxCandidates": 25
}' |
apify call centorprat/trending-token-scanner --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,centorprat/trending-token-scanner"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/ADJvhCcd4uRpdROqs/builds/OCldfSOArRAvAvuhj/openapi.json