Rug-Check

An MCP server that detects potential risks in Solana meme tokens.

python

17

GitHub Stars

python

Language

6 months ago

First Indexed

2 months ago

Catalog Refreshed

Documentation & install

Readme and setup notes from the catalogue, plus a client-ready config you can copy for your MCP host.

Installation

Add the following to your MCP client configuration file.

Configuration

View docs

{
  "mcpServers": {
    "kukapay-rug-check-mcp": {
      "command": "python",
      "args": [
        "path/to/rug-check-mcp/main.py"
      ],
      "env": {
        "SOLSNIFFER_API_KEY": "YOUR_API_KEY"
      }
    }
  }
}

Rug-Check-MCP is an autonomous analyzer that evaluates Solana meme tokens to help AI agents detect rug pulls and unsafe projects. It retrieves token data, processes risk signals, and outputs a structured summary including risk levels, market data, and audit status so you can make informed decisions quickly.

How to use

You use Rug-Check-MCP by running the MCP server locally or via an MCP client, then querying the analysis tool with a Solana token address. The primary tool is analysis_token, which returns a detailed report containing the token’s name, symbol, risk score, market data, supply, and risk breakdowns. You can feed this information into your AI agent to guide decision-making and risk assessment.

Typical workflow:

Start the Rug-Check-MCP server via the configured runtime (Python).
Call the analysis_token tool with the target token address.
Receive a structured dictionary with token_address, token_name, token_symbol, snif_score, market_cap, price, supply_amount, risks, and audit_risk.
Interpret the risk breakdown (high/moderate/low) and audit status to determine safety and potential red flags.

How to install

Prerequisites you need before installation are Python 3.10 or higher and a Solsniffer API key.

Option A: Installing via Smithery (recommended for automated setup)

npx -y @smithery/cli install @kukapay/rug-check-mcp --client claude

Option B: Manual installation

Clone the repository and navigate into it.

git clone https://github.com/kukapay/rug-check-mcp.git
cd rug-check-mcp

Install dependencies using Python’s package manager.

pip install mcp[cli] requests python-dotenv

Configure the MCP client to run the Rug Check server. You’ll set the API key for Solsniffer in the environment.

{ 
  "mcpServers": { 
    "rug-check-mcp": { 
      "command": "python", 
      "args": ["path/to/rug-check-mcp/main.py"], 
      "env": { 
        "SOLSNIFFER_API_KEY": "your_solsniffer_api_key_here" 
      } 
    } 
  }
}

Available tools

analysis_token

Analyzes a Solana token by address and returns a structured report with token details, Snif score, market data, risk breakdowns, and audit status.