# token-rugcheck

> Use this tool when you need to assess the safety of Solana tokens before trading, as it provides real-time risk analysis by cross-referencing multiple sources and generating comprehensive three-layer reports. It takes a token as input and outputs a detailed report, including machine verdict, LLM analysis, and raw on-chain evidence. Ideal for use cases where instant verification is crucial, such as high-frequency trading or automated investment platforms.

Canonical page: https://skillsregistry.net/skills/aethercore-dev-token-rugcheck  
JSON: https://api.skillsregistry.net/v1/skills/aethercore-dev-token-rugcheck

## Description

MCP server for real-time Solana token risk analysis. Cross-references RugCheck.xyz, DexScreener, and GoPlus Security to generate three-layer reports: machine verdict → LLM analysis → raw on-chain evidence. Live on Solana mainnet with USDC micropayments ($0.02/audit). Give any AI agent the ability to check if a token is safe before trading.

## Trust

- **Trust score (0–1):** 0.33
- **Verification tier:** scanned
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** finance
- **Updated:** 2026-09-19

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/tf7udpwbg2)
- **Repository:** <https://github.com/AetherCore-Dev/token-rugcheck>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "aethercore-dev-token-rugcheck"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/aethercore-dev-token-rugcheck` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/aethercore-dev-token-rugcheck/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt