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ChainAware Behavioural Prediction MCP Server

io.github.ChainAware/chainaware-behavioral-prediction-mcp
AI-powered tools to analyze wallet behaviour prediction, fraud detection and rug pull prediction.
healthy
status
14
tools exposed
2776ms
connect latency
c244aa290109
schema fingerprint

Tools (14)

predictive_fraud
🔮 Predictive Fraud Detection Tool 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
predictive_fraud_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
predictive_behaviour
🔍 Predictive Behaviour Analysis Tool 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
predictive_behaviour_batch
Schedule a batch audit (behavioral prediction) 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
predictive_rug_pull
🪂 Predictive Rug‑Pull Detection Tool 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. —
credit_score
🔮 Credit Score Tool AI-driven blockchain analytics evaluate the crypto trust score for each account by reviewing inflows and outflows from Ethereum accounts alongside other blockchain data. Credit Scoring tool combines AI, analytics, crypto fraud scores, and social graph analysis to assess
token_rank_list
🪂 Token Rank List Tool 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
token_rank_single
🪂 Token Rank Single Tool Similar to TokenRank List,Token Rank analyzes the community of token holders and ranks every token by the strength of its holders. Except the token rank and token details the token rank single tool fetches the best holders their details and its globalRank alongside
run_token_audit
🚀 Run Token Audit Requests a Token Audit for a given token contract or returns already calculated audit data for requested token. This tool is "get-or-create": it first checks if a completed audit already exists for this contract, and if so returns the FULL risk report immediately. If n
get_token_audit_result
🪂 Get Token Audit Result Fetches the current status or final results of a previously triggered Token Audit job for a given contract address and chain. This is the SECOND step of the audit workflow, used to poll for and retrieve the full risk report after "Run Token Audit" has been called.
agents_trust_score_list
🪂 Agent Trust Score List Tool The ChainAware Agent Trust Score is a 0-1000 score that measures how safe it is to interact with any ERC-8004 registered AI agent. Unlike voting-based reputation systems - where agents can upvote each other to manufacture trust - the Agent Trust Score is derive
agents_trust_score_single
🪂 Agent Trust Score Single Tool Similar to Agent Trust List, Agent Trust Score Single is a 0-1000 score that measures how safe it is to interact with any ERC-8004 registered AI agent. Unlike voting-based reputation systems - where agents can upvote each other to manufacture trust - the Agen
check_job_status
Check the progress of a scheduled batch calculation job. Returns counts only (completed, failed, pending) — no wallet data. Call this when the user asks whether a job is done or how it is progressing. If status is 'processing' or 'pending', inform the user and do not call get_job_results
get_job_results
Retrieve the results of a completed or partially completed batch job. Only call this when check_job_status shows status is 'completed' or 'partial'. Returns a list of completed wallet addresses and the shared chain/network — use these to query the main backend for actual wallet analysis

Endpoint

https://prediction.mcp.chainaware.ai/sse
Category: AI & LLM · Last checked: 2026-08-15T09:30:51Z

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