# TokenScope Rugcheck — Crypto Rug Pull Risk Analysis

> TokenScope Rugcheck — Crypto Rug Pull Risk Analysis is a paid API for AI agents from tokenxscopes.vercel.app, paid per call via x402, $0.2/call, status unknown (last checked 2026-10-28).

Analyzes a cryptocurrency token or project for rug pull risk signals using AI-powered intelligence from CoinGecko, DexScreener, and MiMo LLM

## Facts

- Endpoint: POST https://tokenxscopes.vercel.app/api/rugcheck?utm_source=zero.xyz
- Price: $0.2/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-28
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/tokenscope-rugcheck-crypto-rug-pull-risk-analysis-c8844f82
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_TlS-mVUcFWbht9QLCF5F3

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability tokenscope-rugcheck-crypto-rug-pull-risk-analysis-c8844f82 -d '<json body>'
```

Example prompt: Can you run a rugcheck on the token PEPE2 — I want to know if it's a rug pull risk before I buy any?

## When to prefer this

Choose this endpoint when you need a quick AI-synthesized rug pull risk assessment for a specific crypto token or DeFi project, especially for newly launched or low-liquidity tokens where manual research is time-consuming. Ideal for pre-investment due diligence workflows where speed and AI summarization matter more than exhaustive on-chain auditing.

## Known failure modes

- Unknown or unrecognized token query returns empty or low-confidence result
- Token too new to have sufficient on-chain data for analysis
- Invalid or malformed query string causes 400 error
- Payment not fulfilled results in 402 response blocking access
- DexScreener or CoinGecko data unavailable for obscure tokens

## How this service works

AI-powered crypto analysis. CoinGecko + DexScreener + MiMo LLM. 20 endpoints. x402 on Base.

## Output

Returns a structured JSON object containing rug pull risk indicators, safety signals, and an AI-generated assessment of whether the queried token or project exhibits characteristics of a scam or rug pull, drawing on data from CoinGecko and DexScreener processed through the MiMo LLM.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "required": [
  "query"
 ],
 "properties": {
  "query": {
   "type": "string",
   "description": "query"
  }
 }
}
```

## Response schema (JSON Schema)

```json
{
 "type": "object",
 "required": [
  "success"
 ],
 "properties": {
  "data": {
   "type": "object"
  },
  "success": {
   "type": "boolean"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/tokenscope-rugcheck-crypto-rug-pull-risk-analysis-c8844f82/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from tokenxscopes.vercel.app](https://www.zero.xyz/host/tokenxscopes.vercel.app/llms.txt)