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CryptoRugMunch/rug-munch-mcp

by Various

MCP server for Marcus Rug Intel — 19 tools for crypto token risk analysis, rug pull detection, and AI forensics. Works with Claude Desktop, Cursor, Windsurf.

C

MCP

CryptoRugMunch/rug-munch-mcp

Added 1 June 2026

#ai-agent #claude-desktop #crypto #cursor #defi #ethereum #mcp #mcp-server

Overview

This MCP server provides 19 tools for crypto token risk analysis, rug pull detection, and AI forensics. It integrates with Claude Desktop, Cursor, and Windsurf to enable AI-assisted security checks in those environments.

Best for

Best for
Developers and analysts building AI-assisted crypto token risk assessment into their development environments

Use cases

  • Analyzing token contract risk for potential rug pulls
  • Performing AI-assisted forensics on suspicious crypto tokens
  • Integrating crypto risk checks into AI coding assistant workflows

Notes

This MCP server provides 19 tools for crypto token risk analysis, rug pull detection, and AI forensics. It integrates with Claude Desktop, Cursor, and Windsurf to enable AI-assisted security checks in those environments.

0 stars on GitHub. Last updated 2026-03-31. Licensed MIT.

Use cases

  • Analyzing token contract risk for potential rug pulls
  • Performing AI-assisted forensics on suspicious crypto tokens
  • Integrating crypto risk checks into AI coding assistant workflows

Pros

  • Offers a wide set of 19 specialized tools for crypto analysis
  • Works directly with popular AI coding assistants like Claude Desktop and Cursor
  • Open source and written in Python for easy customization

Cons

  • No community traction yet with zero stars on GitHub
  • Requires setup of the MCP server and dependency on Marcus Rug Intel
  • Limited to the tools and data sources provided by the rug-munch system

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Offers a wide set of 19 specialized tools for crypto analysis
  • Works directly with popular AI coding assistants like Claude Desktop and Cursor
  • Open source and written in Python for easy customization

Cons

  • No community traction yet with zero stars on GitHub
  • Requires setup of the MCP server and dependency on Marcus Rug Intel
  • Limited to the tools and data sources provided by the rug-munch system

Pairs with

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