Rug Munch Mcp
Run rug-pull and token risk checks from your agent before you scope a crypto feature, integrate a token, or commit to a Web3 product direction.
Overview
Rug Munch MCP is a MCP server for the Validate phase that exposes 19 tools for rug pull detection, AI forensics, and token risk analysis in your agent.
What is this MCP server?
- 19 MCP tools for rug pull detection, AI forensics, and token analysis
- PyPI package rug-munch-mcp v1.0.1 with stdio transport
- Optional RUG_MUNCH_API_KEY bypasses x402 payment path
- Configurable RUG_MUNCH_API_BASE (default cryptorugmunch.app agent API)
- Crypto risk intelligence surfaced inside the agent workflow
- 19 tools documented for rug pull detection, AI forensics, and token analysis
- MCP package version 1.0.1; stdio via PyPI rug-munch-mcp
- Default API base: https://cryptorugmunch.app/api/agent/v1
What problem does it solve?
Evaluating meme coins and new tokens manually is slow and error-prone, so you scope crypto features without consistent rug-pull signals.
Who is it for?
Indie builders exploring crypto integrations who want agent-native token forensics during idea validation and scope decisions.
Skip if: Regulated funds needing certified audit trails, or founders building non-crypto products with no token exposure.
What do I get? / Deliverables
After installing the MCP server and API config, your agent can run structured token and rug-risk checks before you commit build time or treasury exposure.
- Agent-invoked rug pull and token risk reports
- Scope decisions backed by 19 dedicated risk tools
- Faster no-go signals before crypto build investment
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Journey fit
Due diligence on tokens and contracts belongs in validate when you narrow scope and reject bad bets before full build. scope is the canonical shelf because the 19-tool suite supports go/no-go token analysis, not day-two production monitoring.
How it compares
Crypto risk intelligence MCP with 19 tools, not a general finance ledger or a single static security checklist skill.
Common Questions / FAQ
Who is Rug Munch MCP for?
Solo developers and Web3 experimenters using MCP agents who need rug-pull and token analysis before shipping on-chain features.
When should I use Rug Munch MCP?
Use it during validate and scope when comparing tokens, partnerships, or contract integrations and you need a structured risk pass from the agent.
How do I add Rug Munch MCP to my agent?
Install PyPI `rug-munch-mcp` 1.0.1, add stdio MCP in your client, set RUG_MUNCH_API_KEY if you have one, and optionally override RUG_MUNCH_API_BASE.