# ChainAware Behavioural Prediction MCP Server

> Use this tool when you need to predict and prevent fraudulent activities in cryptocurrency transactions, such as rug pulls, or detect suspicious wallet behavior. The ChainAware Behavioural Prediction MCP Server analyzes wallet behavior to provide AI-powered predictions and alerts, taking in transaction data as input and outputting risk assessments and warnings. It is ideal for use cases where security and trust are paramount, such as in cryptocurrency exchanges, wallets, and trading platforms.

Canonical page: https://skillsregistry.net/skills/chainaware-chain-aware-behavioural-prediction-mcp-server  
JSON: https://api.skillsregistry.net/v1/skills/chainaware-chain-aware-behavioural-prediction-mcp-server

## Description

The Behavioural Prediction MCP Server provides AI-powered tools to analyze wallet behaviour prediction,fraud detection and rug pull prediction.

## Trust

- **Trust score (0–1):** 1.00
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-09-19

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/dppzb2667n)
- **Repository:** <https://github.com/ChainAware/behavioral-prediction-mcp>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "chainaware-chain-aware-behavioural-prediction-mcp-server"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/chainaware-chain-aware-behavioural-prediction-mcp-server` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/chainaware-chain-aware-behavioural-prediction-mcp-server/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt