Behavioral Prediction Mcp
AI-powered tools to analyze wallet behaviour prediction,fraud detection and rug pull prediction.
Install
$ agentstack add mcp-chainaware-behavioral-prediction-mcp ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Links to your public security report.[](https://agentstack.voostack.com/security/report/mcp-chainaware-behavioral-prediction-mcp) Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
🧠 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/] LinkedIn: [https://www.linkedin.com/company/chainaware] Blog: [https://chainaware.ai/blog] Learn: [https://chainaware.ai/learn] Examples: [https://github.com/ChainAware/examples] Featured in: CB Insights Fraud Prevention Market Map for the AI Era — ChainAware recognised as a leading AI-era fraud prevention solution for Web3 (2026). Listed on: BNB Chain AI Landscape — ChainAware listed by BNB Chain as a key AI project in the ecosystem (2025). Listed on: BNB Chain Kickstart — Marketing Tools — ChainAware's Growth Agents and Wallet Marketer featured in the BNB Chain Kickstart programme's Marketing Tools section (2025). Awarded: Google Cloud $250k Grant — ChainAware selected for a $250,000 Google Cloud grant (2025). Selected for: AWS Fintech Accelerator — ChainAware accepted into the AWS Fintech Accelerator programme (2024). Listed on: Safary Club Web3 Growth Landscape — Growth Tools — ChainAware featured in the Growth Tools for Web3 Projects category (2024).
mcp-name: io.github.ChainAware/chainaware-behavioral-prediction-mcp
📖 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.
Backtesting verified: 98% Predictive Fraud Detection accuracy · 90.1% Rug Pull Detection accuracy
> 🏆 ChainAware is featured in the CB Insights Fraud Prevention Market Map for the AI Era — recognised as a leading AI-powered fraud prevention solution for Web3 (2026). > 🌐 ChainAware is listed on the BNB Chain AI Landscape — recognised as a key AI project in the BNB Chain ecosystem (2025). > 🚀 ChainAware is listed on BNB Chain Kickstart — Marketing Tools — Growth Agents and Wallet Marketer featured in BNB Chain's official programme for ecosystem growth (2025). > 💰 ChainAware received a $250k Google Cloud Grant — selected by Google Cloud for infrastructure and AI development (2025). > ☁️ ChainAware was accepted into the AWS Fintech Accelerator — selected by AWS for its Fintech Accelerator programme (2024). > 🌱 ChainAware is featured in the Safary Club Web3 Growth Landscape — Growth Tools — listed in the Growth Tools for Web3 Projects category (2024).
⚙️ 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% backtesting 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):
```json { "message": "string", // e.g. “Success” or error description "walletAddress": "string", // blockchain wallet address that was analyzed "chain": "string", // blockchain network identifier (e.g. ETH, BNB,POLYGON,TON,BASE, TRON, HAQQ) "status": "string", // classification result (e.g. “Fraud” | “Not Fraud” | “New Address”) "probabilityFraud": "0.00–1.00", // decimal fraud probability score (string to preserve precision)
"token": "string | null", // optional token associated with the check (may be null) "lastChecked": "ISO-8601 timestamp", // last time the wallet risk analysis was executed
"forensicdetails": { "cybercrime": "string", // indicator score for cybercrime activity "moneylaundering": "string", // indicator score for money laundering activity "numberofmaliciouscontractscreated": "string", // number of malicious contracts deployed by this wallet "gasabuse": "string", // gas abuse indicator "financialcrime": "string", // financial crime indicator "darkwebtransactions": "string", // interaction with darkweb-linked wallets "reinit": "string", // reinitialization exploit indicator "phishingactivities": "string", // phishing activity indicator "fakekyc": "string", // fake KYC related activity "blacklistdoubt": "string", // suspected blacklist association "fakestandardinterface": "string", // fake ERC interface indicator "datasource": "string", // source of forensic intelligence (may be empty) "stealingattack": "string", // stealing attack indicator "blackmailactivities": "string", // blackmail activity indicator "sanctioned": "string", // sanction exposure indicator "maliciousminingactivities": "string", // malicious mining indicator "mixer": "string", // interaction with mixing services "faketoken": "string", // fake token creation or usage indicator "honeypotrelatedaddress": "string" // interaction with honeypot-related addresses }, "checked_times": 0, // integer — number of times this wallet has been analyzed
"createdAt": "ISO-8601 timestamp", // record creation timestamp "updatedAt": "ISO-8601 timestamp", // record last update timestamp
"sanctionData": [ { "category": "string | null", // sanction category (may be null) "name": "string | null", // sanction list name "description": "string | null", // sanction description "url": "string | null", // source URL for sanction information "isSanctioned": false, // boolean — whether the wallet is officially sanctioned "createdAt": "ISO-8601 timestamp", // sanction record creation timestamp "updatedAt": "ISO-8601 timestamp" // sanction record last update timestamp } ] }
Error cases:
• `403 Unauthorized` → invalid `apiKey`
• `400 Bad Request` → malformed `network` or `walletAddress`
• `500 Internal Server Error` → temporary downstream failure
---
### 2. Batch Predictive Fraud Detection Tool
**ID:** `predictive_fraud_batch`
**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 in batch.
Schedule a batch fraud calculation job for a list of wallet addresses.
Use this when the user provides a CSV or list of addresses to analyse.
Returns a job_id and signature immediately — report the job_id to the user and store both job_id and signature in context, they are required for all follow-up calls.
Do NOT poll or wait for results after scheduling.
➡️ Example Use Cases:
• Run fraud batch for this list of addresses on ETH network ?
• What is the fraudulent status of this addresses on BNB ?
**Inputs:**
| Name | Type | Required | Description |
| --------------- | ----------------- | -------- | ------------------------------------------------------------------------- |
| `apiKey` | string | ✅ | API key for authentication |
| `network` | string | ✅ | Blockchain network (`ETH`, `BNB`,`POLYGON`,`TON`,`BASE`, `TRON`, `HAQQ`) |
| `addresses` | array[objects] | ✅ | The list ofwallet address to evaluate |
**Outputs (JSON):**
```json
{
"message": "Job scheduled successfully.",
"job_id": "0fc5897a-ad64-4f21-88b5-1274d1cfec46",
"signature": "260866090d88bf61bdfb54f0533fe876bfd8ded7339691c50ada9de59a48124a",
"total_items": 5,
"chunks_enqueued": 1,
"status": "pending"
}
Error cases:
• 403 Unauthorized → invalid apiKey • 400 Bad Request → malformed network or walletAddress • 500 Internal Server Error → temporary downstream failure ---
3. 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 description
"walletAddress": "string", // blockchain wallet address analyzed
"status": "string", // fraud classification result (e.g. “Fraud” | “Not Fraud” | “New Address”)
"probabilityFraud": "0.00–1.00", // decimal probability score indicating fraud risk
"token": "string | null", // optional token context for the analysis
"chain": "string", // blockchain network identifier (e.g. ETH, BNB,BASE,HAQQ,SOLANA)
"lastChecked": "ISO-8601 timestamp", // last time the wallet was analyzed
"forensic_details": {
"cybercrime": "string", // indicator of cybercrime association
"money_laundering": "string", // money laundering activity indicator
"number_of_malicious_contracts_created": "string", // malicious contracts deployed by wallet
"gas_abuse": "string", // abnormal gas usage indicator
"financial_crime": "string", // financial crime activity indicator
"darkweb_transactions": "string", // interaction with darkweb-linked wallets
"reinit": "string", // contract reinitialization exploit indicator
"phishing_activities": "string", // phishing activity indicator
"fake_kyc": "string", // fake KYC interaction indicator
"blacklist_doubt": "string", // suspected blacklist association
"fake_standard_interface": "string", // fake token interface indicator
"data_source": "string", // source of forensic intelligence
"stealing_attack": "string", // stealing attack indicator
"blackmail_activities": "string", // blackmail activity indicator
"sanctioned": "string", // sanction exposure indicator
"malicious_mining_activities": "string", // malicious mining activity indicator
"mixer": "string", // interaction with mixing services
"fake_token": "string", // fake token creation/use indicator
"honeypot_related_address": "string" // honeypot contract interaction indicator
},
"categories": [
{
"Category": "string", // wallet interaction category (e.g. DeFi, NFT, Bridge)
"Count": 0 // number of transactions/interactions in this category
}
],
"riskProfile": [
{
"Category": "Risk_Profile", // willingnes to take risk object
"Balance_age": 0.0 // 1-10 willingnes to take risk value
}
],
"segmentInfo": "string (JSON encoded)", // serialized JSON containing protocol engagement flags (e.g "{\"Maker\":0,\"Aave_borrow\":0,\"Aave_lend\":1,\"Lido\":0,\"Uniswap\":1,\"Compound_lend\":0,\"Compound_borrow\":0}")
"experience": {
"Type": "string", // descriptor label (e.g. “Experience”)
"Value": 0 // numeric experience score level
},
"intention": {
"Type": "string", // descriptor label (e.g. “Intentions”)
"Value": {
"Prob_Lend": "Low | Medium | High",
"Prob_Trade": "Low | Medium | High",
"Prob_Game": "Low | Medium | High",
"Prob_NFT": "Low | Medium | High",
"Prob_Stake_ETH": "Low | Medium | High",
"Prob_Borrow": "Low | Medium | High",
"Prob_Gamble": "Low | Medium | High",
"Prob_Stake": "Low | Medium | High",
"Prob_Yield_Farm": "Low | Medium
…
## Source & license
This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.
- **Author:** [ChainAware](https://github.com/ChainAware)
- **Source:** [ChainAware/behavioral-prediction-mcp](https://github.com/ChainAware/behavioral-prediction-mcp)
- **License:** MIT
- **Homepage:** https://ChainAware.ai
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.