Rug Munch Intelligence — MCP Server
MCP ServerFree# Rug Munch Intelligence — MCP Server [](https://modelcontextprotocol.io) [](https://cryptorugmunch.app/api/agent/v1/status) [](https://
Capabilities5 decomposed
token risk assessment
Medium confidenceThis capability evaluates the risk associated with a cryptocurrency token by providing a quick risk score from 0 to 100, along with a recommendation. It utilizes a combination of on-chain data analysis and social media sentiment analysis to generate the score, allowing users to make informed decisions before transacting. The architecture leverages a microservices approach, where the risk assessment is performed in real-time through API calls to the Rug Munch Intelligence backend.
Integrates social media sentiment analysis with on-chain data to provide a comprehensive risk score, unlike traditional methods that rely solely on historical price data.
More comprehensive than basic token analysis tools as it combines multiple data sources for risk evaluation.
batch token risk evaluation
Medium confidenceThis capability allows users to assess the risk of up to 20 tokens simultaneously, providing a batch risk score and recommendations for each token. It employs efficient API calls to process multiple requests in parallel, reducing the time needed for evaluations. The architecture is designed to handle bulk requests seamlessly, utilizing asynchronous processing to enhance performance.
Utilizes asynchronous API calls to efficiently handle multiple token evaluations in a single request, unlike many tools that process tokens sequentially.
Faster than competitors by processing batch requests concurrently, reducing overall evaluation time.
deployer wallet analysis
Medium confidenceThis capability analyzes the history of a token's deployer wallet to identify patterns of behavior, such as whether the deployer has a history of rug pulls. It employs a combination of on-chain transaction analysis and historical data mining to assess the deployer's credibility. The analysis is performed through dedicated API endpoints that aggregate and analyze wallet activity over time.
Focuses specifically on deployer wallet behavior, providing insights that are often overlooked by standard token analysis tools.
More thorough than traditional tools by providing historical context on deployers, which is crucial for risk assessment.
social media osint analysis
Medium confidenceThis capability retrieves and analyzes social media presence and red flags associated with a token, providing insights into community sentiment and potential risks. It leverages APIs to gather data from various social media platforms and applies natural language processing to identify negative sentiment or warnings. The architecture allows for real-time data collection and analysis, ensuring timely insights.
Combines social media sentiment analysis with token evaluation, offering a unique perspective on community perceptions that is often absent in traditional analysis.
Provides a more holistic view of token risks by integrating social sentiment, unlike standard risk assessment tools.
coordinated buying pattern detection
Medium confidenceThis capability detects patterns of coordinated buying activity for a token, which can indicate potential manipulation or pump-and-dump schemes. It analyzes transaction data to identify unusual spikes in buying activity and correlates them with wallet addresses. The implementation uses advanced statistical methods to flag suspicious patterns, providing users with alerts on potential risks.
Employs statistical analysis to identify coordinated buying patterns, providing insights that are often missed by standard transaction monitoring tools.
More sophisticated than basic transaction analysis tools by focusing on behavioral patterns indicative of market manipulation.
Capabilities are decomposed by AI analysis. Each maps to specific user intents and improves with match feedback.
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Best For
- ✓crypto traders looking for quick risk evaluations
- ✓crypto analysts managing diverse portfolios
- ✓investors concerned about the credibility of token deployers
- ✓investors looking to understand community sentiment
- ✓traders concerned about market manipulation
Known Limitations
- ⚠Risk scores are based on available data and may not account for all market factors
- ⚠Requires internet access for API calls
- ⚠Limited to 20 tokens per request
- ⚠May incur higher costs due to multiple evaluations
- ⚠Analysis is limited to available historical data
- ⚠May not capture recent deployer activities immediately
Requirements
Input / Output
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Repository Details
About
# Rug Munch Intelligence — MCP Server [](https://modelcontextprotocol.io) [](https://cryptorugmunch.app/api/agent/v1/status) [](https://cryptorugmunch.app/.well-known/x402) **19 tools for crypto token risk intelligence.** Detect rug pulls, honeypots, and scams before your agent transacts. Works with Claude Desktop, Cursor, Windsurf, and any MCP-compatible client. ## What It Does | Tool | What | Price | |------|------|-------| | `check_token_risk` | Quick risk score (0-100) + recommendation | $0.04 | | `check_token_risk_premium` | Full breakdown + deployer + social OSINT | $0.10 | | `check_batch_risk` | Up to 20 tokens at once | $0.30 | | `check_deployer_history` | Deployer wallet analysis — serial rugger? | $0.06 | | `get_token_intelligence` | Complete token profile (price, holders, LP) | $0.06 | | `get_holder_deepdive` | Top holders, concentration, sniper detection | $0.10 | | `get_social_osint` | Social media presence and red flags | $0.06 | | `get_kol_shills` | KOL/influencer shill detection | $0.06 | | `get_coordinated_buys` | Detect coordinated buying patterns | $0.04 | | `check_blacklist` | Community blacklist check | $0.02 | | `check_scammer_wallet` | Known scammer wallet check | $0.02 | | `get_market_risk_index` | Global market risk overview | $0.02 | | `get_serial_ruggers` | Known serial rugger wallets | $0.02 | | `marcus_quick` | AI verdict — Claude Sonnet 4 quick analysis | $0.15 | | `marcus_forensics` | AI forensics — full Claude Sonnet 4 investigation | $0.50 | | `marcus_ultra` | AI deep analysis — Claude Opus 4 | $2.00 | | `marcus_thread` | AI analysis thread for X/Twitter | $1.00 | | `watch_token` | 7-day webhook monitoring for risk changes | $0.20 | | `get_api_status` | Service health + accuracy metrics (free) | Free | ## Quick Start ### Install ```bash pip install rug-munch-mcp ``` ### Claude Desktop Add to `~/Library/Application Support/Claude/claude_desktop_config.json`: ```json { "mcpServers": { "rug-munch": { "command": "rug-munch-mcp", "env": {} } } } ``` ### Cursor / Windsurf Add to your MCP config: ```json { "rug-munch": { "command": "python3", "args": ["-m", "rug_munch_mcp"] } } ``` ### From Source ```bash git clone https://github.com/CryptoRugMunch/rug-munch-mcp cd rug-munch-mcp pip install -e . rug-munch-mcp ``` ## Payment Endpoints are paid via **x402 USDC micropayments** on Base mainnet. When you call a paid tool, the API returns HTTP 402 with payment details. x402-compatible clients handle this automatically. Alternatively, set an API key to bypass x402: ```json { "mcpServers": { "rug-munch": { "command": "rug-munch-mcp", "env": { "RUG_MUNCH_API_KEY": "your-key-here" } } } } ``` ## Supported Chains Solana, Ethereum, Base, Arbitrum, Polygon, Optimism, Avalanche ## Architecture ``` Your Agent (Claude, Cursor, etc.) ↓ MCP stdio rug-munch-mcp (this package) ↓ HTTPS cryptorugmunch.app/api/agent/v1/* ↓ x402 payment (if needed) Rug Munch Intelligence API ↓ 240K+ scans, 114K+ flagged tokens, AI forensics ``` ## Other Integration Methods - **x402 Direct**: [x402-trading-agent](https://github.com/CryptoRugMunch/x402-trading-agent) — Example Python agent - **AgentKit Plugin**: [rug-agent-kit](https://github.com/CryptoRugMunch/rug-agent-kit) — Coinbase AgentKit integration - **A2A**: `https://cryptorugmunch.app/.well-known/agent.json` - **OpenAPI**: `https://cryptorugmunch.app/api/agent/v1/openapi.json` ## Links - **API Status**: https://cryptorugmunch.app/api/agent/v1/status - **Discovery**: https://cryptorugmunch.app/.well-known/mcp.json - **Docs**: https://cryptorugmunch.app/api/agent/v1/skill.md - **GitHub**: https://github.com/CryptoRugMunch ## License MIT
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