ChainAware Behavioural Prediction MCP
ChainAware Behavioural Prediction MCP Details
The ChainAware Behavioural Prediction MCP is an MCP-based server that provides AI-powered tools to analyze wallet behaviour prediction, fraud detection, and rug pull prediction. Designed for Web3 security and DeFi analytics, it enables developers and platforms to integrate risk assessment, predictive wallet behavior insights, and rug-pull detection through MCP-compatible clients. The server exposes three specialized tools and uses Server-Sent Events (SSE) for real-time responses, helping safeguard DeFi users, monitor liquidity risks, and score wallet or contract trustworthiness. Access to production endpoints is API-key gated, reflecting a private backend architecture that supports secure, scalable risk analytics across wallets, contracts, and pools.
Use Case
Use the MCP server to embed AI-driven wallet risk analysis into dApps, wallets, and analytics platforms. Typical scenarios include computing fraud risk scores for addresses, predicting user actions, and assessing rug-pull risk for pools or contracts. Example usage includes leveraging the predictive_rug_pull tool to anticipate liquidity risk or integrating the Predictive Fraud Detection Tool for early warnings on a given wallet. See the code examples in the documentation for concrete usage patterns with MCP clients.
Available Tools (3)
Examples & Tutorials
Node.js Example
import { MCPClient } from "mcp-client";const client = new MCPClient("https://prediction.mcp.chainaware.ai/");
const result = await client.call("predictive_rug_pull", {
apiKey: "your_api_key",
network: "BNB",
walletAddress: "0x1234..."
});
console.log(result);
Python Example
from mcp_client import MCPClientclient = MCPClient("https://prediction.mcp.chainaware.ai/")
res = client.call("chat", {"query": "What is the rug pull risk of 0x1234?"})
print(res)
Frequently Asked Questions
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The MCP server requires an API key for production usage. Production endpoints are accessed via the SSE-based MCP client configuration. The service is public tools – private backend, meaning access is controlled and authenticated. All tools adhere to the MCP specification and are consumable by MCP clients.
API key required for production usage. Access production endpoints via the MCP server. Use an MCP client (Node.js, Python, or Browser) and follow the configuration guidance in the documentation. SSE is used for real-time responses; rate limits may apply.
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