402sentinel-mcp
Enables AI agents to assess counterparty risk scores and enforce payment policies using Circle's x402 payment infrastructure for automatic USDC microtransactions on Base.
Click on "Install 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., "@402sentinel-mcpAssess counterparty 0xabc for 10 USDC payment."
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.
402sentinel-mcp
MCP tools that let your AI agent check an x402 counterparty's risk before it
pays — and turn that risk into an enforceable wallet spending policy. Give it a
payTo address, get back a 0–100 risk score + an allow / review / block
decision, scored from on-chain settlement behaviour on Base (address age,
facilitator-aware payer diversity, settlement maturity) + a delivery-outcome
flywheel, with honest confidence/coverage.
Tools — vet the seller:
assess_counterparty($0.002) — risk score + decision + a ready-to-applyrecommended_policyassess_counterparty_deep($0.02) — same, scans more on-chain historyrecommend_policy($0.002) — decision + wallet-ready spending policy (caps, denylist, approval)report_outcome(free) — after paying, report delivery to train the reliability flywheel
Tools — vet the payment itself (buyer-side):
firewall($0.002) — should YOUR agent make THIS payment now? Catches fraudulent routing (payTo swapped vs the address you usually pay), drain velocity, overcharge, and injection-sourced instructions.agent_id+ a wallet-ownership signature are attached automatically from your configured wallet — trusted routing history with no extra steps.firewall_record(free) — seed your agent's payment history so the firewall has a behavioural baseline.firewall_outcome(free) — after a verdict, report what actually happened (fraud / legit / …) so the firewall learns which signals are predictive and downweights noisy ones (safety signals stay deterministic).
It's a thin client for the hosted service at https://402sentinel.com — the scoring model and facilitator-identification logic live server-side (closed); this package only forwards the request and pays for it, so it's open source.
Quickstart — gate a payment in 5 lines
Before your agent pays any x402 counterparty, ask the firewall; if it doesn't say
allow, don't pay. No MCP needed — any x402 client works (here, Circle's):
import { GatewayClient } from "@circle-fin/x402-batching/client";
const sentinel = new GatewayClient({ chain: "base", privateKey: process.env.AGENT_KEY });
const { data } = await sentinel.pay("https://402sentinel.com/api/firewall", { method: "POST", body: {
payment: { payto_address: target, amount, resource_url },
context: { source: "web_content", untrusted_text: pageYouActedOn } } }); // pass what you scraped
if (data.decision !== "allow") throw new Error(`402Sentinel ${data.decision}: ${data.recommended_action}`);
// …safe to pay `target`.That one $0.002 call catches fraudulent routing (payTo swapped vs the address you
usually pay), prompt-injection payments (a payTo that appeared in untrusted_text),
drains, overcharges, and sanctioned/illicit counterparties.
In an MCP framework (Claude, Cursor, …) instead, just add the server — your agent gets all 7 tools by name (see Configure below):
{ "mcpServers": { "402sentinel": { "command": "402sentinel-mcp", "env": { "CLIENT_PRIVATE_KEY": "0x…" } } } }Related MCP server: acuris-agent-guard
Install
npm i -g @kaditang/402sentinel-mcpConfigure
Add to your MCP client (Claude Desktop, Cursor, etc.):
{
"mcpServers": {
"402sentinel": {
"command": "402sentinel-mcp",
"env": {
"CLIENT_PRIVATE_KEY": "0x... // a Base wallet with USDC in its Circle Gateway balance"
}
}
}
}Paid calls cost from $0.002 (shallow) to $0.02 (deep), paid automatically
in USDC via x402 (Circle Gateway, gas-free on Base) from the configured wallet.
report_outcome is free. (CLIENT_PRIVATE_KEY is only needed for the paid tools.)
Use
The agent calls it before authorizing a payment:
assess_counterparty({
target: { payto_address: "0x..." },
payment_context: { amount: 10, asset: "USDC" },
policy: { block_at_score: 70, review_at_score: 40 }
})
→ { decision: "review", risk_score: 52, confidence: 0.41, coverage: {...},
dimensions: [...], recommendation: "...",
recommended_policy: { action: "limit", max_payment_usdc: 5, daily_cap_usdc: 15,
add_to_denylist: false, require_human_approval: true } }block/deny→ don't payreview/limit→ cap exposure / escrow (userecommended_policyfor the caps)allow→ proceed
recommend_policy(...) returns just the decision + recommended_policy — apply
max_payment_usdc / daily_cap_usdc / add_to_denylist directly to your agent
wallet's spending limits. After paying, call report_outcome({ assessment_id, outcome }) to improve future scores.
Disclaimer
Algorithmic risk signal, informational only — not advice, not an endorsement, and not an accusation about any party. Scores are probabilistic estimates from limited public on-chain data and heuristics, and may misclassify. Do your own due diligence; don't rely on it as your sole basis to pay or refuse. See https://402sentinel.com/terms.
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