Rug Check MCP Server

An MCP server that detects potential risks in Solana meme tokens, helping AI agents avoid rug pulls and unsafe projects.

Local serverstdioPython

What is the Rug Check MCP MCP server?

Rug Check MCP MCP server is a locally run integration for AI assistants that speak the Model Context Protocol. An MCP server that detects potential risks in Solana meme tokens, helping AI agents avoid rug pulls and unsafe projects.

What you get

  • Token Analysis Tool — The analysis_token tool retrieves and processes Solana token data from the Solsniffer API
  • Structured Output — Returns detailed token information including name, symbol, Snif score, market cap, price, supply, risks, and audit status

What the assistant can call

Once Rug Check MCP is connected, these are the calls the assistant has available:

  • Description — Analyzes a Solana token based on its address
  • Input — token_address (string) - The Solana token address to analyze
  • Output — A dictionary containing:
  • token_address — Token address
  • token_name — Token name
  • token_symbol — Token symbol
  • snif_score — Solsniffer risk score (0-100)
  • market_cap — Market capitalization in USD
  • price — Token price in USD
  • supply_amount — Total supply of the token
  • risks — High, moderate, and low risk details with counts and descriptions
  • audit_risk — Audit status (mint/freeze disabled, LP burned, top 10 holders)

Setting it up

@smithery/cli on npm is all you need. Most clients run it directly, so configuration is a few lines and a restart.

Configuration and credentials

You will need one environment variable: SOLSNIFFER_API_KEY. The server will not start without them, which is usually why the tools fail to appear on a first run. Keep credentials in your client's env block or a secrets manager rather than in a file you might commit.

  • Python 3.10 or higher - A Solsniffer API key (sign up at Solsniffer to obtain one)

Choosing this one

Among the developer tooling options, the useful question is rarely "what can it do" but "what does it cost you to run" — permissions, credentials, and how much of your context its toolset consumes. Rug Check MCP's toolset — Description, Input, Output and 11 more — is a fair guide to whether it matches your workflow. It is maintained by kukapay; worth a glance at recent repository activity before you build anything load-bearing on it.

SyncDev reviews every entry in this directory against the project's own documentation before publishing, and revisits them as servers change.

Before you rely on it

  • It runs with your machine's permissions. That is convenient and also the reason to think about what you point it at before you approve a tool call.
  • With 14 tools registered it takes up a noticeable share of the context window; turn it off in projects that never touch Rug Check MCP.
  • Missing credentials fail quietly in some clients — if no tools show up, check the environment block first.
  • MCP clients confirm each tool call by default. Leave that on until you have watched what the rug check mcp mcp server does with a few real requests.

Available tools

ToolWhat it does
DescriptionAnalyzes a Solana token based on its address.
Inputtoken_address (string) - The Solana token address to analyze.
OutputA dictionary containing:
token_addressToken address
token_nameToken name
token_symbolToken symbol
snif_scoreSolsniffer risk score (0-100)
market_capMarket capitalization in USD
priceToken price in USD
supply_amountTotal supply of the token
risksHigh, moderate, and low risk details with counts and descriptions
audit_riskAudit status (mint/freeze disabled, LP burned, top 10 holders)
Price$0.000297
Risks- High (3 risks):

How to install the Rug Check MCP MCP server

3. **Client Configuration**:

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

Configuration as documented by the project. Restart the client after saving.

Configuration

  • Python 3.10 or higher - A Solsniffer API key (sign up at Solsniffer to obtain one)
VariableDescriptionRequired
SOLSNIFFER_API_KEYCredential the server authenticates with.Yes

Example prompts to try

  • Use Rug Check MCP to Description.
  • Use Rug Check MCP to Input.
  • Use Rug Check MCP to Output.

Frequently asked questions

It connects Rug Check MCP to MCP-compatible AI assistants such as Claude and Cursor, exposing 14 tools (Description, Input, Output, and more) that the assistant can call on your behalf. Instead of copying data back and forth by hand, the assistant works with Rug Check MCP directly.