Arsenal Decision Engine 🛡️

MCP serverAI & models

This integration lets your AI check the risk of providing liquidity in decentralized finance before any funds are committed. It calculates impermanent loss and the price range where a position breaks even, returning the numbers instantly. Access is paid through a Lightning-based paywall.

Use Arsenal Decision Engine 🛡️ in Claude, ChatGPT or Ahel Desktop

Free. Sign in, add Arsenal Decision Engine 🛡️ and connect your AI. About a minute.

Also: Claude Code · Cursor · Codex

Then ask your AI: use the evaluate pool tool from Arsenal Decision Engine 🛡️

Details

Available today. Use it from your connected AI after setup.

Add the integration, then share the liquidity position or pool you are considering and ask your AI for the risk breakdown. Keep in mind that requests go through a Lightning paywall, so payment is required.

Arsenal Decision Engine 🛡️Start free

What your AI can do with it

  • Weigh the risk of a liquidity position before entering it
  • Calculate impermanent loss for a liquidity pool deposit
  • Find the price range where a position breaks even
  • Estimate net returns for a liquidity position
  • Return risk results instantly, in a single calculation step

Install Arsenal Decision Engine 🛡️

The server’s own address, for the clients that take one directly. Or connect Ahel once and every client you use reads it from one address, with the account kept on Ahel rather than in each client’s config.

  • Claude Code

    claude mcp add --transport http --scope user arsenal-decision-engine 'https://api.arsenal-quant.com/mcp'

    Run it once in your project, then open /mcp to approve any sign-in the server asks for.

  • Claude Desktop

    https://api.arsenal-quant.com/mcp

    Add a custom connector in Settings, paste this address, and approve the sign-in.

  • Cursor

    cursor://anysphere.cursor-deeplink/mcp/install?name=arsenal-decision-engine&config=eyJ1cmwiOiJodHRwczovL2FwaS5hcnNlbmFsLXF1YW50LmNvbS9tY3AifQ==

    Open the link and Cursor adds the server at that address.

  • ChatGPT

    https://api.arsenal-quant.com/mcp

    In Settings, enable Developer mode, create an MCP app, and paste this address. Your plan and workspace must allow custom apps.

  • Codex

    codex mcp add arsenal-decision-engine --url 'https://api.arsenal-quant.com/mcp'

    Run it once, then sign in with codex mcp login arsenal-decision-engine if the server asks for an account.

From the project's README

As published by faouzi122/arsenal-quant-project in README.md.

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

Method and raw results are published — backtest script · result data (180 days of Binance ETH/USDC daily closes): 🔬 Breakeven Corridor is a deterministic algebraic boundary (where IL = accumulated yield). Any position whose price ratio stays within [lower_be, upper_be] has R_net > 0 by mathematical definition — not a probabilistic model. 📐 This engine measures; it does not forecast. No predictive-accuracy figure is claimed — read the published result files and judge the method for yourself.


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 standard constant-product / full-range LP positions.

Built for agents. 100 free calls per IP per day — no wallet, no sign-up, custom parameters included. An L402 payment path is implemented in the gateway but is not operational in production: today, the engine is free to use.


What This Engine Does

Before an autonomous agent deploys capital or adjusts a standard constant-product / full-range LP position (such as Uniswap V2 or full-range V3), 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.

Two ways to call it

1. MCP JSON-RPC — the endpoint advertised on the MCP registry

POST https://api.arsenal-quant.com/mcp
{"jsonrpc":"2.0","id":1,"method":"tools/call",
 "params":{"name":"evaluate_pool",
           "arguments":{"apy":0.20,"price_ratio":0.85,"days_held":30}}}

Standard MCP handshake: initialize → tools/list → tools/call. Available over streamable HTTP and stdio.

2. REST convenience route — no MCP client required

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

Both routes run the same calculation and the same quota. Note that /mcp/evaluate is GET-only: a POST to that path returns 405 Allow: GET, because JSON-RPC belongs on /mcp.

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": "<HMAC-SHA256 hex — illustrative placeholder, yours will differ>",
  "layer": "FREE"
}

layer reports how the call was served: FREE while inside the free quota, PREMIUM once an L402 payment has been verified. The call shown above is served as FREE.


Access and Pricing

  • Free tier — evaluate_pool: 100 calls per IP per day, custom parameters included. No Lightning wallet is needed. This is the only tier currently in service.
  • Beyond the free quota: the gateway implements the L402 challenge and returns 402 with a WWW-Authenticate header. The payment rail is not operational in production — invoices issued today are not settleable, and no payment is expected or accepted. Treat the paid tier as announced, not available.
  • GET /mcp/audit/latest: 3 free calls per IP per hour; beyond that the route returns 402. That response documents the protocol; it is not a live payment path.

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 requires a wallet key with send permission to pay an invoice.
# Use a DEDICATED wallet funded with a small working balance, and never the key
# of a wallet holding significant funds. Keep it in the environment, never in code.
LNBITS_PAYMENT_KEY = os.getenv("LNBITS_PAYMENT_KEY")

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_PAYMENT_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 per-call pricing is the intended model

This engine does not prevent losses, and it makes no claim about how much money it saves you. What it does is compute — deterministically, in $\mathcal{O}(1)$ — whether a position sits above or below its breakeven boundary. Each response carries an HMAC tag over the result, which lets the engine detect tampering with its own output; it is a symmetric provenance marker, not a proof a third party can verify independently.

The intended model is per-call pricing, so the cost can be budgeted like any other input. That model is not yet in service: today every call is free.

Tools it offers (1)

What this server listed when Ahel dialed its public endpoint in Oct 2026, with no key and no account of yours. The names are the server’s own.

  • evaluate_pool

Signals

Forks
1
Last commit
Sep 2026
Advanced
Delivery
arsenal-decision-engine MCP server → your Ahel connector (mcp.ahel.ai) → your AI.
Item type
mcp-server
Key
io-github-faouzi122-arsenal-decision-engine
Source
github.com/faouzi122/arsenal-quant-project
Hosted endpoint
https://api.arsenal-quant.com/mcp