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Arsenal Quant Project MCP Server

by Faouzi122
Developer ToolsLow Risk9.9MCP RegistryRemote
Free

Server data from the Official MCP Registry

R_net LP risk evaluator for DeFAI agents. IL + Breakeven Corridor O(1). L402 Lightning paywall.

About

R_net LP risk evaluator for DeFAI agents. IL + Breakeven Corridor O(1). L402 Lightning paywall.

Remote endpoints: streamable-http: https://api.arsenal-quant.com/mcp/evaluate

Security Report

9.9
Low Risk9.9Low Risk

Valid MCP server (1 strong, 1 medium validity signals). No known CVEs in dependencies. Imported from the Official MCP Registry. 1 finding(s) downgraded by scanner intelligence.

Endpoint verified · Open access · 1 issue found

Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.

Permissions Required

This plugin requests these system permissions. Most are normal for its category.

HTTP Network Access

Connects to external APIs or services over the internet.

env_vars

Check that this permission is expected for this type of plugin.

How to Connect

Remote Plugin

No local installation needed. Your AI client connects to the remote endpoint directly.

Add this to your MCP configuration to connect:

{
  "mcpServers": {
    "io-github-faouzi122-arsenal-decision-engine": {
      "url": "https://api.arsenal-quant.com/mcp/evaluate"
    }
  }
}

Documentation

View on GitHub

From the project's GitHub README.

Arsenal Decision Engine 🛡️

The Risk-Validation Layer for Autonomous AI Agents (DeFAI)

Arsenal-Quant-Project MCP server smithery badge

Empirical Validation (180-Day Binance ETH/USDC Data): 🏆 100% Breakeven Corridor Reliability. Positions that stayed within the calculated corridor completed their lifecycle with a positive net yield ($R_{net} > 0$). 🎯 82% to 97% Mid-Checkpoint Risk Level Accuracy in predicting final position health.


Mission

Transform DeFi uncertainty into deterministic, actionable risk metrics for autonomous agents. We do not run stateful trading bots or generate speculative prediction signals; we provide a stateless risk middleware layer that agents query before deploying or maintaining concentrated liquidity positions.

Built for agents, priced for agents. Pay per decision via Lightning Network (L402).


What This Engine Does

Before an autonomous agent deploys capital or adjusts a Uniswap V3 LP position, it submits the pool parameters (APY, price ratio, days held) to our API. The engine computes the exact mathematical risk, the net return ($R_{net}$), and the dynamic Breakeven Corridor bounds.

  • No LLMs. No hallucinations. Pure algebraic calculation.
  • Complexity: $\mathcal{O}(1)$ time and memory.
  • Latency: $< 15\text{ms}$ local execution.

Agent Request (HTTP GET)

https://api.arsenal-quant.com/mcp/evaluate?apy=0.20&price_ratio=0.85&days_held=30

Engine Response (JSON Contract)

{
  "impermanent_loss_pct": 0.3292,
  "accumulated_yield_pct": 1.6438,
  "r_net_pct": 1.3146,
  "il_to_yield_ratio": 0.2,
  "risk_level": "LOW",
  "breakeven_corridor": {
    "lower_ratio": 0.6941,
    "upper_ratio": 1.4407,
    "interpretation": "Position remains profitable if price ratio stays within [0.6941, 1.4407]"
  },
  "inputs": {
    "apy": 0.2,
    "price_ratio": 0.85,
    "days_held": 30
  },
  "source": "Arsenal Decision Engine v2.0",
  "oracle_signature": "b5dce8268fe762fa66ffccc083b02e9b65801888cdf76004ff22b648ea80869b",
  "layer": "PREMIUM"
}

API Pricing (Dynamic L402)

  • Free Tier: First 3 requests per IP/hour are free.
  • Low/Moderate Risk Positions: 50 Sats per evaluation.
  • High/Critical Risk Positions: 500 Sats per evaluation.

Python Integration Example

import urllib.request
import urllib.error
import json
import re
import os

API_URL = "https://api.arsenal-quant.com/mcp/evaluate?apy=0.20&price_ratio=0.85&days_held=30"
LNBITS_URL = "https://demo.lnbits.com"
LNBITS_ADMIN_KEY = os.getenv("LNBITS_ADMIN_KEY", "your_key_here")

def query_risk_oracle():
    req = urllib.request.Request(API_URL, method="GET")
    req.add_header("x-agent-id", "autonomous-lp-bot")

    try:
        with urllib.request.urlopen(req) as resp:
            return json.loads(resp.read().decode('utf-8'))
    except urllib.error.HTTPError as e:
        if e.code == 402:
            auth_header = e.headers.get("WWW-Authenticate")
            macaroon = re.search(r'token="([^"]+)"', auth_header).group(1)
            invoice = re.search(r'invoice="([^"]+)"', auth_header).group(1)

            pay_req = urllib.request.Request(
                f"{LNBITS_URL}/api/v1/payments",
                data=json.dumps({"out": True, "bolt11": invoice}).encode(),
                headers={"X-Api-Key": LNBITS_ADMIN_KEY, "Content-Type": "application/json"}
            )
            with urllib.request.urlopen(pay_req) as pay_resp:
                preimage = json.loads(pay_resp.read().decode())["preimage"]

            retry_req = urllib.request.Request(API_URL, method="GET")
            retry_req.add_header("Authorization", f"L402 {macaroon}:{preimage}")
            retry_req.add_header("x-agent-id", "autonomous-lp-bot")

            with urllib.request.urlopen(retry_req) as final_resp:
                return json.loads(final_resp.read().decode('utf-8'))
        else:
            raise

if __name__ == "__main__":
    evaluation = query_risk_oracle()
    print(f"Risk Level     : {evaluation['risk_level']}")
    print(f"R_net          : {evaluation['r_net_pct']:+.4f}%")
    print(f"Breakeven      : [{evaluation['breakeven_corridor']['lower_ratio']}, {evaluation['breakeven_corridor']['upper_ratio']}]")

Developer Integration

  • Integration cookbook & MCP guides: COOKBOOK.md
  • MCP auto-discovery card: https://api.arsenal-quant.com/.well-known/mcp/server-card.json

Why L402? (Proof of Savings)

If this engine protects your agent from a $50,000 Impermanent Loss wipeout, a 500 Satoshi ($0.30) deterministic risk-validation call is not a cost — it is a mathematical insurance policy.

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Source CodeRemote Endpoint

Details

Published July 6, 2026
Version 2.0.0
0 installs
Remote Plugin

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