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Marcus Rug Intel — AgentKit Plugin 🛡️

Add rug pull detection to any Coinbase AgentKit trading agent.

Coinbase x402 Ecosystem

Your agent checks every token for scams before trading. Costs $0.04 per check.

Install

pip install coinbase-agentkit rug-munch-agentkit

Or from source:

git clone https://github.com/CryptoRugMunch/rug-agent-kit.git
cd rug-agent-kit
pip install -e .

Quick Start

from coinbase_agentkit import (
    AgentKit, AgentKitConfig,
    CdpEvmWalletProvider, CdpEvmWalletProviderConfig,
    wallet_action_provider, erc20_action_provider,
)
from rug_munch_agentkit import rug_munch_action_provider

# Set up wallet
wallet_provider = CdpEvmWalletProvider(CdpEvmWalletProviderConfig(
    api_key_id="YOUR_CDP_KEY_ID",
    api_key_secret="YOUR_CDP_KEY_SECRET",
    wallet_secret="YOUR_WALLET_SECRET",
    network_id="base-mainnet",
))

# Create agent with Rug Munch risk intelligence
agentkit = AgentKit(AgentKitConfig(
    wallet_provider=wallet_provider,
    action_providers=[
        rug_munch_action_provider(),   # ← Risk checks before trades
        wallet_action_provider(),
        erc20_action_provider(),
    ],
))

# Use with LangChain
from coinbase_agentkit_langchain import get_langchain_tools
tools = get_langchain_tools(agentkit)

# Or use directly
result = agentkit.run_action("check_token_risk", {
    "token_address": "7GCihgDB8fe6KNjn2MYtkzZcRjQy3t9GHdC8uHYmW2hr",
    "chain": "solana",
})

Available Actions

Action Cost Description
check_token_risk $0.04 Risk score, honeypot detection, SAFE/CAUTION/AVOID
check_batch_risk $0.30 Batch scan up to 20 tokens
check_deployer_history $0.06 Deployer rug count, classification
get_holder_deepdive $0.10 Sniper detection, whale tracking
get_token_intelligence $0.06 Price, volume, LP lock, holder stats
marcus_quick_analysis $0.15 AI forensic verdict (Claude Sonnet 4)
watch_token_risk $0.20 7-day webhook monitoring

How It Works

Your LLM Agent
    ↓ "Should I buy token X?"
AgentKit calls check_token_risk
    ↓
Marcus Rug Intel API returns:
    risk_score: 85, recommendation: "AVOID"
    ↓
Agent: "This token has freeze authority and the deployer
        rugged 3 previous tokens. Skipping."

The agent automatically uses check_token_risk before executing trades when the LLM determines a risk check is appropriate. The action descriptions are designed so LLMs naturally invoke them in trading contexts.

Configuration

# Required: API key for authenticated access (or use x402 auto-payment)
export MRI_API_KEY="your-api-key"

# Optional: Override API URL
export MRI_API_BASE="https://cryptorugmunch.app/api/agent/v1"

x402 Payment (No API Key Needed)

If you don't have an API key, the API uses x402 protocol — your agent pays per-request with USDC on Base or Solana. Just ensure your agent's wallet has USDC.

With LangChain

from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

llm = ChatOpenAI(model="gpt-4o")
tools = get_langchain_tools(agentkit)

agent = create_react_agent(llm, tools)

# The agent will automatically check risk before trading
response = agent.invoke({
    "messages": [{"role": "user", "content":
        "Check if token 7GCihgDB8fe6KNjn2MYtkzZcRjQy3t9GHdC8uHYmW2hr is safe to buy"
    }]
})

Links

⚠️ Note: This project was formerly known as CryptoRugMunch. The $CRM token is not affiliated with Marcus Rug Intel.

License

MIT