Behavioral Prediction

🧠 ChainAware Behavioural Prediction MCP Server

MCP Server Name: ChainAware Behavioural Prediction MCP

Category: Web3 / Security / DeFi Analytics

Status: Public tools – Private backend

Access: By request (API key)

Server URL: [https://prediction.mcp.chainaware.ai/sse]

Repository: [https://github.com/ChainAware/behavioral-prediction-mcp]

Website: [https://chainaware.ai/]

Twitter: [https://x.com/ChainAware/]

mcp-name: io.github.ChainAware/chainaware-behavioral-prediction-mcp

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📖 Description

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

Developers and platforms can integrate these tools through the MCP protocol to safeguard DeFi users, monitor liquidity risks, and score wallet or contract trustworthiness.

All tools follow the Model Context Protocol (MCP) and can be consumed via MCP-compatible clients.

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⚙️ Available Tools

1. Predictive Fraud Detection Tool

ID: predictive_fraud

Description: This AI‑powered algorithm forecasts the likelihood of fraudulent activity on a given wallet address before it happens (≈98% accuracy), and performs AML/Anti‑Money‑Laundering checks. Use this when your user wants a risk assessment or early‑warning on a blockchain address.

➡️ Example Use Cases:

• Is it safe to intercant with vitalik.eth ?
• What is the fraudulent status of this address ?
• Is my new wallet at risk of being used for fraud?  

Inputs:

Name	Type	Required	Description
apiKey	string	✅	API key for authentication
network	string	✅	Blockchain network (ETH, BNB,POLYGON,TON,BASE, TRON, HAQQ)
walletAddress	string	✅	The wallet address to evaluate

Outputs (JSON):

{
    "message": "string",              // Human‑readable status message
    "walletAddress": "string",        // hex address 
    "status": "Fraud",                // Fraudelent status (Fraud,Not Fraud,New Address)
    "probabilityFraud": "0.00–1.00",  // Decimal probability
    "token": "string",                //
    "lastChecked": "ISO‑8601 timestamp",
    "forensic_details": {             // Deep forensic breakdown
    /* ...other metrics... */
    },
    "createdAt": "ISO‑8601 timestamp", 
    "updatedAt": "ISO‑8601 timestamp"
}

Error cases:

• `403 Unauthorized` → invalid `apiKey`  
• `400 Bad Request` → malformed `network` or `walletAddress`  
• `500 Internal Server Error` → temporary downstream failure  

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2. Predictive Behaviour Analysis Tool

ID: predictive_behaviour

Description: This AI‑driven engine projects what a wallet address intentions or what address is likely to do next, profiles its past on‑chain history, and recommends personalized actions.

Use this when you need:

  • Next‑best‑action predictions and intentions(“Will this address deposit, trade, or stake?”)  
  • A risk‑tolerance and experience profile  
  • Category segmentation (e.g. NFT, DeFi, Bridge usage)  
  • Custom recommendations based on historical patterns

➡️ Example Use Cases:

• “What will this address do next?”  
• “Is the user high‑risk or experienced?”  
• “Recommend the best DeFi strategies for 0x1234... on ETH network.”

Inputs:

Name	Type	Required	Description
apiKey	string	✅	API key for authentication
network	string	✅	Blockchain network (ETH, BNB,BASE,HAQQ,SOLANA)
walletAddress	string	✅	The wallet address to evaluate

Outputs (JSON):

{
    "message":           "string",                    // e.g. “Success” or error text  
    "walletAddress":     "string",                    // echoed input  
    "status":            "string",                    // Fraudelent status (Fraud,Not Fraud,New Address)  
    "probabilityFraud":  "0.00–1.00",                 // decimal fraud score  
    "lastChecked":       "ISO‑8601 timestamp",        // e.g. “2025‑01‑03T16:19:13.000Z”  
    "forensic_details":  { /* dict of forensic metrics */ },  
    "categories":        [ { "Category":"string", "Count":int }, … ],  
    "riskProfile":       [ { "Category":"string", "Balance_age":float }, … ],  
    "segmentInfo":       "JSON‑string of segment counts",  
    "experience":        { "Type":"Experience", "Value":int },  
    "intention":         {                              
    "Type":"Intentions",  
    "Value": { "Prob_Trade":"High", "Prob_Stake":"Medium", … }  
    },  
    "protocols":         [ { "Protocol":"string","Count":int }, … ],  
    "recommendation":    { "Type":"Recommendation", "Value":[ "string", … ] },  
    "createdAt":         "ISO‑8601 timestamp",  
    "updatedAt":         "ISO‑8601 timestamp"  
}

Error cases:

• `403 Unauthorized` → invalid `apiKey`  
• `400 Bad Request` → malformed `network` or `walletAddress`  
• `500 Internal Server Error` → temporary downstream failure  

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3. Predictive Rug‑Pull Detection Tool

ID: predictive_rug_pull

Description: This AI‑powered engine forecasts which liquidity pools or contracts are likely to perform a “rug pull” in the future. Use this when you need to warn users before they deposit into risky pools or to monitor smart‑contract security on-chain.

➡️ Example Use Cases:

• “Will this new DeFi pool rug‑pull if I stake my assets?”  
• “Monitor my LP position for potential future exploits.”  

Inputs:

Name	Type	Required	Description
apiKey	string	✅	API key for authentication
network	string	✅	Blockchain network (ETH, BNB, BASE, HAQQ)
walletAddress	string	✅	Smart contract or liquidity pool address

Outputs (JSON):

{
  "message": "Success",
  "contractAddress": "0x1234...",
  "status": "Fraud",
  "probabilityFraud": 0.87,
  "lastChecked": "2025-10-25T12:45:00Z",
  "forensic_details": { /* dict of on‑chain metrics */ }, 
  "createdAt": "2025-10-25T12:45:00Z",
  "updatedAt": "2025-10-25T12:45:00Z"
}

Error cases:

• `403 Unauthorized` → invalid `apiKey`  
• `400 Bad Request` → malformed `network` or `walletAddress`  
• `500 Internal Server Error` → temporary downstream failure  

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4. Token Rank List Tool

ID: token_rank_list

Description: TokenRank analyzes the community of token holders and ranks every token by the strength of its holders. The stronger the token holders, the stronger the token! Use this when you need to know token rank of a token or tokens or compare between different categories and chains. You can use search,filter and sort and pagination which returns a list of tokens.

➡️ Example Use Cases: – “Which is the best token on AI Token category?”
– “Compare x token in ETH chain and BNB chain?”

Inputs:

Name	Type	Required	Description
limit	string	✅	Number of items ot fetch during pagination
offset	string	✅	Page number(offset) during pagination
network	string		Blockchain network to filter (ETH, BNB, BASE, SOLANA)
sort_by	string		Sort the returnet tokens based on (e.g.: 'communityRank')
sort_order	string		'ASC' or 'DESC' sorting the value of sort_by
category	string		Filter based on category of the token (e.g. 'AI Token','RWA Token','DeFi Token','DeFAI Token','DePIN Token')
contract_name	string		Search based on contract name

Outputs (JSON):

  {
    "message": "string",                    // e.g. “Successfully fetched records” or error description
    "data": {
      "total": 0,                           // integer — total number of matching contracts
      "contracts": [
        {
          "contractAddress": "string",       // unique contract or mint address (chain-specific format)
          "contractName": "string",          // human-readable token name
          "ticker": "string",                // token symbol (usually uppercase, but not guaranteed)
          "chain": "string",                 // blockchain network (e.g. SOLANA | ETH | BNB | BASE)
          "category": "string",              // primary category label 

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*README truncated. [View full README on GitHub](https://github.com/chainaware/behavioral-prediction-mcp).*