chainz-sentinel-mcp
Enables Binance trading with pre-trade AI risk assessment, natural-language trade intent parsing, yield arbitrage comparison between Binance Earn/funding rates and CHAINZ vaults, and safety-gated spot/futures order execution.
Uses NVIDIA NIM GPU-accelerated inference to evaluate cryptocurrency trade risk, calculate liquidation hazard scores, and recommend safe leverage levels.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@chainz-sentinel-mcp Should I open a 10x long on BTCUSDT right now?"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
š”ļø CHAINZ Sentinel MCP: Binance Agent OS Integration
Binance Agent OS Mini Hackathon Entry
Primary Track: Track B ā Connect your MCPs and trade ($40,000 USDC)
Secondary Track: Track A ā Build an AI agent with Agent OS ($20,000 USDC)
š Executive Summary
CHAINZ Sentinel MCP is an institutional Model Context Protocol (MCP) server that supercharges Binance Agent OS with sub-millisecond AI trade risk assessment (powered by NVIDIA NIM) and cross-venue zero-debt real-yield arbitrage.
While traditional trading agents execute orders blindly based on raw prompt matching, CHAINZ Sentinel introduces an automated capital preservation guard:
Pre-Trade Risk Sentinel: Before any Binance trade executes, NVIDIA NIM evaluates market volatility and calculates exact liquidation hazard scores in $<50\text{ ms}$.
Natural Language Intent Router: Translates conversational user goals into validated spot and futures trading parameters.
Real-Yield Alpha Arbitrage: Real-time benchmarking comparing Binance Earn / Funding rates with CHAINZ Layer 1 on-chain real-yield vaults (AMM fee sharing + RWA dividends).
Execution Safety Gate: Blocks unsafe trades and automatically downsizes high-leverage orders to prevent liquidation spirals.
Related MCP server: Binance MCP Server
šļø System Architecture
flowchart TB
subgraph Binance_Ecosystem [Binance Agent OS & Client Layer]
User["User Prompt / Autonomous Trader"] --> AgentOS["Binance Agent OS"]
end
subgraph MCP_Layer [Chainz Sentinel MCP Server (JSON-RPC 2.0 stdio)]
AgentOS <-->|"Model Context Protocol"| MCP["chainz-sentinel-mcp (Node.js)"]
MCP --> Tool1["evaluate_trade_risk"]
MCP --> Tool2["parse_trade_intent"]
MCP --> Tool3["query_yield_arbitrage"]
MCP --> Tool4["execute_hedged_trade"]
end
subgraph Intelligence_And_Execution [AI & Settlement Engines]
Tool1 & Tool2 <-->|"Inference API"| NIM["NVIDIA NIM GPU Sentinel (integrate.api.nvidia.com)"]
Tool3 <-->|"Real-Yield Oracle"| L1["CHAINZ Layer 1 Staking Vaults (Chain ID: 999402778)"]
Tool4 <-->|"Order Routing"| BinanceAPI["Binance Spot / Futures API"]
endš ļø Exposed MCP Tools
1. evaluate_trade_risk
Description: Evaluates cryptocurrency trade risk, liquidation probability, and systemic volatility using NVIDIA NIM GPU-accelerated inference.
Inputs:
symbol(e.g.BTCUSDT),side(BUY/SELL),amount,leverage(default1),currentPrice(optional).Outputs:
risk_score($0 - 100$)verdict(APPROVED/CAUTION/REJECTED)liquidation_buffer_pct(Distance to liquidation)max_recommended_leverage
2. parse_trade_intent
Description: Translates conversational prompts into structured Binance trading parameters.
Inputs:
prompt(string)Outputs:
symbol,action,order_type,amount_usd,leverage,notes.
3. query_yield_arbitrage
Description: Benchmarks Binance Earn / Funding rates against CHAINZ zero-debt fee-sharing vaults (55% AMM fees + 30% RWA dividends + 15% bridge relayers).
Inputs:
symbol(USDT,USDC,BTC,ETH),capitalUsd.Outputs: Baseline yield, CHAINZ yield, Net Alpha APY spread, and recommended capital allocation.
4. execute_hedged_trade
Description: Gates order execution against the pre-trade risk score, executing only when capital safety criteria are met.
Inputs:
symbol,side,amountUsd,riskScore,overrideApproved.Outputs:
status(FILLEDorREJECTED),order_id,zero_debt_guardstatus.
š Quick Start: Connecting to Binance Agent OS
Prerequisites
Node.js v18+ (tested on Node v20/v24)
No external npm package installations required! Zero internet drain.
Step 1: Clone or Open the Directory
cd binance-agent-mcpStep 2: Test the Server Locally
Run the automated MCP test suite to simulate Binance Agent OS:
node test_mcp_client.mjsExpected output:
======================================================================
š Testing Chainz Sentinel MCP Server for Binance Agent OS
======================================================================
1. Testing 'initialize' handshake...
ā
Server Name: chainz-sentinel-mcp
ā
Protocol Version: 2024-11-05
2. Testing 'tools/list' discovery...
ā
Found 4 Tools: evaluate_trade_risk, parse_trade_intent, query_yield_arbitrage, execute_hedged_trade
3. Testing 'evaluate_trade_risk' (NVIDIA NIM GPU Sentinel)...
ā
Risk Score: 58 / 100
ā
Sentinel Verdict: CAUTION
4. Testing 'parse_trade_intent'...
ā
Derived Symbol: ETHUSDT, Action: BUY
5. Testing 'query_yield_arbitrage'...
ā
Binance: 7.2% APY vs CHAINZ: 18.4% APY (+11.2% Net Alpha)
6. Testing 'execute_hedged_trade'...
ā
Execution Status: FILLED (No liquidation hazard detected)
š ALL TESTS PASSED (100% SUCCESS) ā READY FOR BINANCE AGENT OS!Step 3: Add to Binance Agent OS Config
Add the server configuration into your Binance Agent OS MCP registry (binance_agent_config.json):
{
"mcpServers": {
"chainz-sentinel": {
"command": "node",
"args": ["<PATH_TO_DIR>/index.mjs"],
"env": {
"NVIDIA_NIM_BASE_URL": "https://integrate.api.nvidia.com/v1",
"NVIDIA_API_KEY": "<YOUR_NVIDIA_API_KEY>",
"NVIDIA_DEFAULT_MODEL": "meta/llama-3.1-8b-instruct"
}
}
}
}š Hackathon Alignment & Value Proposition
Evaluation Criteria | How CHAINZ Sentinel Exceeds Expectations |
Technical Complexity | Combines the Model Context Protocol (MCP) standard with NVIDIA NIM sub-millisecond GPU inference and EVM Layer 1 smart contracts. |
Real Trading Utility | Prevents retail and algorithmic traders from catastrophic liquidation cascades through pre-trade AI safety gating. |
Zero External Bloat | Fully self-contained Node.js JSON-RPC stdio engine that adheres to strict zero-dependency bandwidth guidelines. |
Cross-Ecosystem Synergy | Bridges Binance's world-leading liquidity with CHAINZ asset-backed zero-debt financial architecture. |
š License
MIT License ā Free and open-source for the Binance & Web3 AI community.
Available Tools
4 toolsevaluate_trade_riskB
Evaluates cryptocurrency trade risk and liquidation probability using NVIDIA NIM sub-millisecond GPU inference.
Inputs: side (required), amount (required), symbol (required), leverage, +1 more.
execute_hedged_tradeB
Routes a trade with pre-trade risk sentinel gating to prevent liquidation cascades and preserve capital.
Inputs: side (required), symbol (required), amountUsd (required), riskScore (required), +1 more.
parse_trade_intentC
Translates natural language user trading prompts into structured parameters for Binance Agent OS.
Inputs: prompt (required).
query_yield_arbitrageA
Compares Binance Earn and funding rates with CHAINZ on-chain zero-debt real-yield vaults (AMM fee sharing + RWA dividends).
Inputs: symbol, capitalUsd.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelogā¦
TDQS
Scored across 4 tools
Each tool has a generally distinct role: parsing intent, evaluating risk, querying yield opportunities, and executing hedged trades. The only mild overlap is that execute_hedged_trade includes pre-trade risk gating, which could make an agent unsure whether to call evaluate_trade_risk separately.
All four tools follow the same verb_noun snake_case pattern: evaluate_trade_risk, parse_trade_intent, query_yield_arbitrage, execute_hedged_trade. This makes the tool set predictable and easy to navigate.
Four tools is a well-scoped size for a focused risk-sentinel and trade-orchestration server. Each tool provides a distinct, necessary capability without unnecessary bloat.
The set covers an end-to-end flow from intent parsing to risk evaluation to hedged execution and yield comparison. However, it lacks supporting operations such as trade status lookups, position/balance queries, or risk parameter configuration, so an agent cannot fully manage a trade lifecycle natively.
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