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
Security Report
Valid MCP server (1 strong, 1 medium validity signals). No known CVEs in dependencies. Imported from the Official MCP Registry.
2 tools verified ยท Open access ยท No issues 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.
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"
}
}
}Documentation
View on GitHubFrom the project's GitHub README.
Arsenal Decision Engine ๐ก๏ธ
The Risk-Validation Layer for Autonomous AI Agents (DeFAI)
Method and raw results are published โ backtest script ยท result data (180 days of Binance ETH/USDC daily closes): ๐ฌ 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 โ not a probabilistic model. ๐ This engine measures; it does not forecast. No predictive-accuracy figure is claimed โ 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 โ 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 โ 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 โ tools/list โ tools/call. Available over
streamable HTTP and stdio.
2. REST convenience route โ 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 โ 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 โ
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
402with aWWW-Authenticateheader. The payment rail is not operational in production โ 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 returns402. 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 โ deterministically, in $\mathcal{O}(1)$ โ 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.
Reviews
No reviews yet
Be the first to review this server!
More Developer Tools MCP Servers
Fetch
Freeby Modelcontextprotocol ยท Developer Tools
Web content fetching and conversion for efficient LLM usage
Git
Freeby Modelcontextprotocol ยท Developer Tools
Read, search, and manipulate Git repositories programmatically
Toleno
Freeby Toleno ยท Developer Tools
Toleno Network MCP Server โ Manage your Toleno mining account with Claude AI using natural language.
mcp-creator-python
Freeby mcp-marketplace ยท Developer Tools
Create, build, and publish Python MCP servers to PyPI โ conversationally.
MarkItDown
Freeby Microsoft ยท Content & Media
Convert files (PDF, Word, Excel, images, audio) to Markdown for LLM consumption
MCP Marketplace
Freeby mcp-marketplace ยท Developer Tools
Search and install MCP servers from inside your AI client.
